Dynamics in Logistics

In this paper, we introduce the concept of “shared resources” which is used to prevent structural resource scarceness in the field of logistics. Due to the unlimited growth of value creation activities, capacity limits of infrastructures (for traffic, communication and energy) are reached and emission rights become scarce. However, public infrastructure investments decrease while private investments become more difficult since individual private investors are unable to provide sufficient capital. In conclusion, innovative resource providing concepts are needed in logistics. The major innovation of this chapter is the proposal of an innovative resource management concept to make today’s logistics systems and processes sustainable with respect to the upcoming scarceness of input resources (e.g. infrastructure) and output resources (e.g. emission rights).

Within the logistics sector, access limitation problems have so far only been handled via bottom-up coordination. With the implementation of the European Union’s Emission Trading Scheme (EU ETS) a regulatory top-down approach for coordinating the use of shared resources got implemented. We analyze the new regulations using three core characteristics to examine whether the market-based mechanism could be used to coordinate similar economic problems. Insights about the major issues of sharing problems illustrate potential effects on the logistics sector.

The term intermodal transport subsumes transport processes in which the carried goods are packed/stored in loading units like containers or swap bodies or trucks or trailers and these loading units are moved by truck in the local area distribution and collection as well as by train (or barge) during the main-haul process phase. In this paper, we are going to investigate the hypothesis that the reformation of the management and administration of intermodal transport chains can contribute to the promotion of this environmental-friendly and highway-disburdening kind of long distance freight transport. We propose to change the administration, and to manage a combined transport chain as a so-called shared system. The primary goal of the here reported research is to analyze the general applicability of the sharing principle in intermodal freight transport.

Manufacturing systems are complex networks of material flow. Complex network theory has been used as a descriptive and empirical research tool for various network types. However, due to the distinct origin of the various investigated networks (e.g., social networks, biological networks, the Internet), it is not clear if there is a meaningful application of network measures in manufacturing systems. This chapter investigates network modeling and network measures in manufacturing systems, and categorizes them according to their type of research.

In this paper, we describe a simulation for an automotive manufacturing process using automated guided vehicles (AGVs). The simulation is used to optimize a generalized factory model layout using multi-objective evolutionary algorithms. The Pareto front of the optimization is analyzed, and layouts are compared to the industry standard transfer line in terms of objectives that include capital cost, energy usage, and product throughput. We seek to determine from the results whether genetic algorithms are a feasible tool for the optimization of manufacturing automobiles.

This paper applies the concept of inter-firm resources to inter-organizational information systems that are shared between enterprises within production and logistics networks. The paper focuses on challenges during collaborative initiation, development, implementation, operation, and maintenance as well as termination of such shared information systems. The availability of instruments for improving all these life cycle phases of shared information systems is discussed based on the implementation of an EPCIS-based data exchange infrastructure within an automotive production network.

Modern production lines typically consist of several components, which have to be installed with high precision in order to work together harmoniously. Upon installation of this equipment, a vast number of drill holes need to be marked. This stage of the setup process of a factory is performed manually at present and henceforth it is both time-consuming and error-prone. Within this work, we present a method to accomplish this task autonomously by means of possibly multiple mobile robots. To this end, we propose a hierarchical event based control strategy for the mixed-integer optimal control problem and provide insight into real-time capable solution methods. Moreover, an experimental setup utilizing a Leica AT901-LR laser tracker and a KUKA youBot is studied. This case study shows that the process can be performed autonomously satisfying the desired marking precision and yet be completed within a shorter time frame thus reducing the costs.

The requirements of transport processes have become increasingly complex due to shorter transit times, the individual qualities of shipments, and higher amounts of small sized orders. Especially in courier and express services providing same day deliveries, the high degree of dynamics even increases this complexity. To ensure reliable and flexible planning and control of transport processes, we present a reactive and proactive agent-based system to support the dispatching of logistic transport service providers. Beside the application in simulated real-world processes of our industrial partners, this paper focuses on the impact and relevance of shortest-path queries in the system. We compare the application of state-of-the-art algorithms and investigate the effects of high speed shortest-path computations in agent-based negotiations. The results prove that efficient shortest-path algorithms are an essential key component in agent-based control of dynamic transport processes.

This chapter presents a new automated full-case Order Picking (OP) system. A dynamic fuzzy logic will be used to determine the average expected throughput time of the system and to find the mathematical equations, which describe the system. This system has been developed as a new technique that minimizes OP time and other non-value adding tasks and maximizes performance. This new system will improve productivity, accuracy, and speed of order delivery in comparison with conventional automated full-case picking systems.

Application of autonomous control for shop-floor scheduling by considering real-time control of material flows is advantageous to those assembly lines with dynamic and uncertain circumstances. Among several potential processors with computing and communication capabilities—for representing autonomous material carriers—wireless sensor nodes seem as promising objects to be applied in practice. For realizing autonomy in making scheduling and routing-control decisions some methodologies need to be embedded in the nodes. Among several experimented methodologies, e.g., artificial intelligence, genetic algorithm, etc., in the context of a doctoral research, in this current special case of assembly scenario, the queuing theory and its simple equations seem quite suitable. For instance, employment of Little’s law for calculating and analysis of simple queuing structures is a favorable method for autonomous pallets in real shop-floors. Concerning the simplicity and inexpensive computing loads of such a rule, it suits the best to the low capacity wireless sensors in developing pilot prototypes of autonomous carriers. Little’s law can be used to estimate the current waiting times of alternative stations and try to find a non-decreasing order of operations to improve the performance record (e.g., makespan) of the entire assembly system. To develop a pilot prototype, some wireless sensors—representing pallets in practice—are connected to a simulated assembly scenario via the TCP/IP protocol to evaluate the feasibility of realizing autonomous pallets in the practice of shop-floor control. Nevertheless, wireless nodes are distributed objects, so the use of data sharing for transferring low data between each other and respectively low energy consumption is necessary.

In this paper, we propose a framework for modeling of logistic systems with an emphasis on model transformation. Due to the complexity of logistic systems, their models are bound to consist of many heterogeneous components on various descriptive levels from the requirement definition to the platform-specific implementation. To cover these phenomena in a comprehensive way, our approach provides two main concepts: First, we introduce logistic models that may be the combination of a variety of component models, which in turn may be of different types, i.e., they may be specified by means of different modeling methods. Second, we offer model transformations that allow to translate logistic models of one type into logistic models of another type whenever needed (for example, to bridge the gap between visual platform-independent models and textual platform-specific models or to facilitate the interaction of component models of different types).

In general, rental articles circulate in closed logistic systems between the lender and one or more dynamically changing customers. The planning processes, related to the allocation of those articles to customer orders, are a challenging task. This is especially the case, if orders have a close temporal distance, as the corresponding order execution takes place between the poles of high customer demands and the lender’s economic interests. This paper introduces an autonomously controlled distribution system for rental articles that takes over both the allocation of articles to orders and the related logistic planning. At this, the focus lies on the results of first benchmarks and an estimation of the related potential for savings. A company from the field of event logistics serves as an application example for the distribution approach.

Container terminal is a dynamic interface worldwide. It portrays national capability in trading with outsider via seaborne. This research aims at measuring operational risk within container terminal besides its efficiency. By means of identify and apply DEA technique towards operationalisation of supply chain and risk, this research is providing final outcome with no adjusted risk rank order of decision-making unit (DMU). A panel data from 6 container terminals in Peninsular Malaysia are retrieved from 2003 until 2010. In turn, 8 years of data with 6 terminals resulting 48 container terminal DMUs. Slacks-Based Measure (SBM) and Super Slacks-Based Measure (SSBM) are used for risk solution. The findings of the research express efficiency based on the allocation of resources must be optimised to achieve optimum outcome. SBM and SSBM findings indicate that no adjusted risks are significantly related with size, planning, equipment and volume of cargoes. This is critical as container segments give a significant contribution to terminal operators. In addition, container terminal is competitive industry, as Malaysia is competing not only with neighbouring countries but also with Asian countries in particular and the world in general.

Maintenance of the offshore wind turbines imposes high cost, effort, and risk on the wind farm owners. Therefore, it is highly demanded to make the wind turbine maintenance activities more reliable and cheaper. To achieve this goal, the focus of current research is to investigate how the available data through the life cycle of an offshore wind turbine can be utilized to improve the maintenance activities. In this work, it will be investigated, how to integrate information feedbacks from the operation phase of an offshore wind turbine to the maintenance stage. A comparison will be done afterwards between the proposed method and existing data-driven maintenance approaches in wind turbine and other industries such as aviation and shipping.

The empty container management is one of the most popular problems in shipping. The container repositioning is very expensive and shippers cannot generate profit with it, so it is very important for shippers to have an efficient container management. This paper discusses the problem of repositioning empty containers in a cheap way and it shows up a possible optimization for the problem. First, the paper introduces the subject of the empty container management. This section is followed by a problem description and a modified Inland Empty Container Depot (IDEC) model based on Mittal, which solves the container problem. Afterwards, there is a description of the further modification of the model for the empty container management problem in hinterland, which is based on the modified IDEC. This model additionally considers the container transportation by barge and train, while the IDEC only uses the truck. In the last chapter of the paper, some possible results are presented.

This chapter investigates a vehicle routing problem with synchronization requirements for the services provided to customers. The problem finds an application in the home health care branch, where staff members of health care agencies have to be routed and services at patients’ homes have to be scheduled. The latter can involve simultaneous services, where two staff members have to serve one patient jointly, and services with given precedence, where two service operations have to be provided to a patient within a given time distance. This paper presents a Benders’ decomposition method for solving this problem exactly.

Vehicle routing comprises a variety of fleet disposition problems. We compare the performance of a homogeneous fleet of vehicles with the performance of a mixed (or heterogeneous) fleet of vehicles consisting of big but slow trucks and small but fast vans. We consider a scenario with operation starting time synchronization, e.g., a scenario in which two vehicles have to be assigned to a customer location and both selected vehicles must start their unloading operations at the same time. Within computational simulation experiments, we demonstrate that the fuel consumption as well as the makespan benefit from the deployment of a mixed fleet.

The production of full truck load (FTL) services has no standardisation and industrialisation characteristics today. Despite the anticipated cost increases in road freight transport, a large-scale and cross-company pooling of relation-related transport volumes is not expected in the medium term. The main reason for this situation is the ‘artisanal’ kind of production, characterised by an insurmountable driver vehicle bond (often including trailer) resulting in a tight coupling between the driver’s working time and vehicle operating time. The implementation of the multi-shift operation as presented in this research follows a new, not previously practised implementation process. Due to the fact that individual companies cannot create their own synergies and coordinate individual transports in terms of a sequential multi-layer operation, an enterprise-wide network has to be created. This should be a network in which the ‘industrialised’ full load transport, in the form of broken traffic (encounter traffic and shuttle services), can be mapped. The research results are made available for practise and combined in a model-based framework for modeling transport logistics processes and analyses. In a field experiment, the economic effects of the restructured production processes will be investigated to provide reliability for permanent participation to any company in the network. Finally, after the establishment of the developed transportation network, highly frequented depot links will be tested for their potential of bundling and following shift to rail.

Based on the actual situation of full truck load logistics in Germany and the idea of a reorganization of the transport routes using a cooperative network structure with encounter traffics at depots, we model one simple case to underline the expected advantages in costs and productivity. It turns out that the transport costs and unproductive time decreases drastically in the network structure and as positive side effect the job as truck driver may become more attractive.

This study addresses the problem of optimizing the mixed storage and re-marshalling plans in a block stacking storage system with re-handling. Mixed storage is a storage method in which unit loads of different types are stored in the same bay. The re-marshalling is an activity of moving unit loads from mixed storage to other areas in which unit loads of different types are stored in a segregated way. This removes the need for re-handling during retrieval operations. The objectives of this study are to suggest methods for: (1) estimating the space requirement, including broken space, for mixed and segregated storage; and (2) determining the groups of unit load types to be placed in mixed storage, and the re-marshalling time for each group. Two uncertainties are considered: the types of unit loads to arrive and the times of arrival. A simulation model is used to estimate the space requirement for the two storage methods, and various load composition and arrival time distribution parameters are considered.

In the inland container transportation problem, one trucking company operating a homogeneous fleet of trucks has to move 40-ft. containers. The recent extension to this problem is to introduce two different commodities, namely 20- and 40-ft. containers, instead of only 40-ft. containers. Our objective is to minimize the total travel distance of the trucks for the extended problem. A model is shown and implemented in C++ using IBM ILOG CPLEX solver. Fifteen test instances are created to obtain computational results using our implementation.

In our paper, a general scheme for modeling different logistical systems functioning under uncertainty is presented. It is defined in the terms of so-called semi-Markov drift processes with several continuous components (random walks in non-negative orthant of Eucleadean space). Some examples of this scheme application for modeling and optimization of logistical systems are given: optimal lot sizing taking into account the irregularity of product delivery from a vendor to wholesaler in the multi-echelon distribution system under fixed demand; optimal distribution of a manufactured product to a set of retailers under random demand.

One of the crucial enablers of the fourth industrial revolution is the implementation of autonomy in supply chains. Increased autonomy in logistics adds flexibility and robustness to supply chains. However, decentralized local decision making also creates new challenges since optimization problems now have to be solved in a decentralized manner. This research project proposes to apply agent technology to solve optimization problems in a distributed way in order to maintain efficiency while benifitting from the advantages of decentralization.

Machine-to-Machine (M2M) communication is one of the emerging fields today and expected to play a major role in interconnecting various types of devices for different applications, such as logistics. Mobile communication standards, such as Long Term Evolution Advanced (LTE-A), have high data rate capability and are designed to provide broadband services to the human-based communication. M2M devices in logistics usually transmit small amount of data depending on the application scenario. LTE-A can be optimized to provide better performance of M2M devices in logistics. This paper studies a Relay Node (RN) based solution in LTE-A to integrate M2M devices in mobile cellular networks. Different M2M scenarios are developed for logistics along with normal LTE-A users in our LTE-A simulation model implemented in OPNET Modeler. The simulation results show that the data traffic performance of LTE-A network improves significantly if RN is utilized for aggregation and multiplexing of M2M data traffic in logistics.

Machine-to-machine (M2M) communication is an emerging paradigm in which trillions of intelligent devices are expected to communicate without or with small human intervention. The increasing M2M devices have severe impact on long-term evolution (LTE) data traffics. Moreover, the behavior of M2M traffic also differs from traditional mobile traffic. In future, logistics and transportations are considered to be the main M2M application areas. These applications disparately demand more efficient M2M traffic modeling to reduce end-to-end (E2E) delay between various interconnected machines. This paper investigates several traffic models and highlights the impact of M2M traffic in logistics and transportation on LTE data traffic. We evaluate the overall LTE network performance in terms of E2E delays for file transfer, voice, and video users.

The temperature of chilled and frozen products along the distribution phase must be maintained within close limits to ensure optimum food safety levels. The temperature variation along the vehicle routing sequence is represented by nonlinear functions which depend on the process stage (line haul, unloading at customer’s premises, local displacements, etc.). The usual vehicle routing optimization strategy is generally based on a traveling salesman problem (TSP) sequence, with the objective of minimizing travel distance or time. It is shown in the paper that in order to maintain the temperature variability within adequate restriction limits, other routing strategies, apart from the TSP criterion, should be considered.

Over the past decade, due to its superior characteristics over other data capturing systems, the trend toward implementing radio frequency identification (RFID) technology in real-time production is increasing. However, RFID adoption is still not mature enough to cover today’s production environments’ aspects and needs. This research addresses the significant role of RFID in smart lean manufacturing sustainability and lean digital factories. This paper focuses on expanding the utilization of RFID system beyond tracking to include intelligent real-time control of production operations from the value stream point of view. Therefore a real-time RFID-based dynamic value stream mapping (DVSM) is developed to overcome the limitations of snapshot VSM in order to live monitor the dynamic behavior of production shop-floor (PSF). DVSM is used as a real-time computer-based lean tool that contains different real-time operations control modules, and if-analysis functions to sustain LM practices and to achieve lean aims. An example of the real-time module which runs through DVSM to support LM aims is developed. It is called real-time dispatching priority generator (RT-DPG) module. RT-DPG contains different material flow control rules to live prioritize the material flow in unpredictable dynamic production environments, and thereby real-time jobs dispatching priorities will be more practical and precisely generated to match load-leveling schedule which is based on “Takt-time” and enhance production smoothing to reduce the total cycle time.

Radio frequency identification (RFID) is a well-established approach for tracking and tracing vehicles. So far, researchers and practitioners have focused on track and trace solutions, which apply RFID transponders that are temporarily attached to vehicles. In this paper, we investigate the potential of integrating transponders into vehicles as actual part of the product. Our research indicates that permanent product integration is feasible from the technical point of view and may support a large variety of track and trace scenarios, e.g., vehicle production and logistics as well as customer applications such as toll collections and parking lot solutions.

Transporting of sensitive commodities in strict ambient conditions becomes necessity not only to fulfill regulations but also to maintain their quality and to reduce the rate of losses. Temperature, which mainly affects the transported produce, is controlled by airflow pattern in reefer containers. Consequently, obtaining airflow pattern enables predicting hot spots and then taking the necessary actions to minimize their effects. We present, in this paper, a k-ε simulation model to evaluate airflow pattern in reefer container loaded with bananas. Simulation results predict the place of the hot spots. Moreover, we found that the cooling distribution is improved by modification of the scheme for placing pallets in the container, the so-called chimney layout.

In order to cope with the increasing need for flexibility, today’s material flow systems move toward decentralized and modular approaches. However, operation and control of the majority of such systems are based on manufacturer-specific standards, thus resulting in the loss of their reusability and making the task of integrating two or more such systems a rather complex one. In this paper, we present a software platform for supporting collaboration between partners at designing and testing of heterogeneous decentralized controlled systems, prior to deployment. As a use case scenario, we demonstrate a virtual merge of two remote logistics labs, namely, an electric overhead monorail system pilot plant at institute fml of the Technical University of Munich and a conveyor system at institute FLW of the Technical University of Dortmund.

Operation and maintenance of offshore wind turbines (OWTs) play an important role to guaranty and improve the reliability, availability, and sustainability during the life time of an OWT. Common maintenance approaches from reactive to preventive maintenance show difficulties in being applied throughout offshore wind park operations. In the field of preventive maintenance, the condition-based maintenance shows a significant upturn. This paper gives a valuable insight into a modernized approach to “preactive” measures in different dimensions. To this end, existing approaches for condition-based maintenance are pointed out. Based on this knowledge, a new approach, using existing information and knowledge to encounter relevant events, is introduced. A maintenance strategy by context enables a dynamical adjustment of maintenance time slots based on different information, like, for example, weather, the general condition of a wind turbine, and availability of staff. Finally, the concept will be illustrated with an example.

Due to the European-wide target to reduce greenhouse gas emissions from the transport sector, electric mobility (EM) is considered by many countries to have a high potential to contribute to this reduction. The challenges connected to the extensive introduction of EM are the battery capacity of the vehicles, high procurements costs, and the access to charging infrastructure. Innovative user services associated with EM can contribute to establish this new technology. Therefore, this paper provides a scientific approach to use mobile devices, like e.g., smart phones or tablets, of electric vehicle users as personal energy assistants (PEAs). This PEA supports the charging process for electric vehicles (EV) associated with a specific user. The service contains user-generated loading profiles, the definition of thresholds for electricity rates by the user, battery-protecting charging management, energy-efficient navigation as well as routing assistance to specific charging stations. The communication between mobile device of the vehicle user, electric vehicle, and smart charging infrastructure is enabled by near field communication (NFC). This communication standard ensures an immediate and safe communication that enables services such as mobile payment and a user-specific configuration of the charging infrastructure by a simple gesture. In conclusion and outlook, additional future services will be described that refer, e.g., to a battery health monitoring, a drive style monitoring, and driving style-related rental rates for EV.

The paper presents the food traceability prototype, which was implemented as a pilot application of the FP7 EU project ebbits. The platform architecture, built upon the principles of the Internet of Things (IoT), People, and Services, is described in aspects of the supported interoperability and semantic orchestration of services involved in the food production chain. The platform represents physical objects as digital objects that go through different phases in the production chain. The information produced in each phase is stored by involved actors and could be retrieved back by the consumers through orchestrating services provided by the actors in the production chain. These services are resolved by a product service orchestration, which is supported by a semantic backend.

The brain–computer interface (BCI) system allows us to convert brain activity into meaningful control signals. This article presents an efficient BCI signal classification technique that uses median filtering and wavelet transform (WT) to improve classification performance and reduce computational complexity. In one preprocessing step, median filtering is carried out in order to attenuate noise, and WT is used to extract features that are classified by support vector machines (SVM). The database we use for this purpose is from BCI competition-II 2003 provided by the “University of Technology, Graz.” We show that using these two techniques in series, the classification accuracy can be increased up to 90 %. This method is therefore a very good approach toward designing online BCI and it is not computationally intensive.

The research initiative “Industrie 4.0” (I4.0) of the high-tech strategy announced by the German government targets the deployment of a cyber-physical system (CPS) in production and logistics. Such CPS-based environments are characterized by an increasing number of heterogeneous intelligent autonomous and communicating artifacts tightly integrated with humans. Thus, the human’s role will become a composite factor (“man-in-the-mesh”) for this future CPS environment, playing more than just a simple role inside the control loop. This paper investigates the need of a robust communication between CPS and humans, which includes a clear semantic of the exchanged information. For this purpose, a mediation service and corresponding language are presented. Finally, further research activities are presented.

With deteriorating environment and insufficient energy resource, the electric vehicle has become a solution to reduce the emissions and save the fossil energy. Many automakers begin to develop and research electric vehicles. Most governments support policies to promote the development of electric vehicles. However, the application of the electric vehicle is still in the initial stage (test and demonstration), especially for the electric commercial vehicle (ECV), which carries goods with battery systems. The objective of this paper is to describe an idea, how to apply the ECV in the urban freight transport with analyzing the influential factor.

Freight electric vehicles (EVs) over 3.5 tons are of particular interest to the reduce air pollutants in the urban freight transport sector. However, one main reason why freight transport companies refrain from deploying freight EVs are their higher costs, compared to conventional vehicles. But despite their lower operational costs, the high purchase price of medium duty EVs—which are predominantly used in urban freight transport—renders them uncompetitive, compared to conventional vehicles. One possibility to raise the competitiveness of freight EVs is to increase their range by improving the drivers’ behavior. This is an important leverage, since first tests with passenger EVs indicate that the drivers’ behavior can influence the vehicles range with up to 30 %. Although sufficient literature about eco-drive strategies for conventional freight vehicles exists, these strategies cannot be directly transferred to freight EVs, due to technological differences, such as recuperation. The research of specific strategies for freight EVs has received little attention so far. Thus the objective of this research proposal is to measure, analyze and model the dependency of medium duty freight EVs energy consumption on the drivers’ behavior, by utilizing real world test data.

Sustainability is a modern day requirement toward global supply chains and also in most cases an efficiency challenge for logistic companies. Complementary objectives in decreasing carbon footprint and costs of transports are assumed or claimed, e.g., for an increase in load factors, reduction in transport intervals, and other green transport approaches in scheduling and tour planning. And also conflicting objectives can be identified with a decrease in flexibility due to lower transport intervals and higher load factors, as this research approach shows with a meta-heuristic approach for delivery transports under uncertainty of demand conditions. This uncertainty regarding increasing cost of necessary changes in transport planning due to probabilistic demand changes can be seen as excess flexibility costs. These can lead to increased security stock levels based on bullwhip behavior of logistics deciders, creating an additional green bullwhip effect for supposed sustainable supply chains. Therefore, the overall business and sustainability improvement in measures such as, e.g., reduced delivery intervals are to be evaluated taking this new perspective into account.

Since climate change has already threatened the whole ecological environment worldwide as well as the living surroundings of human beings, positive actions and regulations from governments are proposed and put into practice before the situation reaches the extreme situation in the near future. Among them, the EU-emission trading scheme (EU ETS) offers probably one of the most cost-efficient solutions for companies to realize greenhouse gas emission reduction. In this context, manufacturers and other companies included in ETS are confronted with the trade-off between carbon abatement cost and carbon allowance purchasing cost. The logistics sector, maintaining close business relationships with almost every industrial sector, is not yet directly included into ETS so far but still faces to the challenge of green reformation required by its customers from the manufacture industry and so on. A new market competition is aroused not only in inclusive manufacture industry but also in the logistics sector. This paper is going to introduce the ETS-impacted logistics sections, to discern both challenges and opportunities for logistics providers, and finally to propose effective measures against the current dilemma.

In this paper, we develop a model for the economic travel speed of container ships and show how the travel speed impacts the profit situation as well as the environmental sustainability. Thereby, we differentiate between a cost-optimal and profit-optimal travel speed strategy and show, based on model calculations, how both strategies lead to lower costs as well as lower emissions. Following the dynamic network aspect, we suggest that large container ship companies can adopt both strategies under specific market conditions which allow them to act profitable as well as environmental sustainable.

Freight carriers are often confronted with customers demanding for quick execution of their transport requests. Especially for Small and Mid-size Carriers (SMCs), it is very difficult to deal with the uncertainness pertinent to dynamic planning. Horizontal collaboration may help SMCs to operate more efficiently in such situations by performing Collaborative Transportation Planning (CTP). As shown in the literature referring to static situations, SMCs are able to generate high cost savings due to the exchange of requests. To realize such synergy also in dynamic situations, approaches of CTP must be adapted for Dynamic CTP Problems (DCTPP). In this paper, a DCTPP of a coalition of freight carriers with the same hard planning horizon is presented. A stepwise approach using single event optimization is proposed to solve this problem. Computational studies are presented to identify the cost saving potential of the DCTPP against isolated planning. Furthermore, an analysis of the best times for a new planning is performed.

This paper analyses if the Collaborative Networked Organizations (CNO) concept can bring advantages in organizing the international outbound logistics for SMEs. In the manufacturing domain, the European CNO research has identified benefits from using the concept in traditional supply chains, collaboration in various inbound networks and business eco-systems. Less focus has been made on outbound logistics for delivering products and related service to customers at remote locations. The analysis is based on the conducted company interviews. The interviewed companies have a good record of successful international operations. The used international delivery models are mapped into the taxonomy of well-known outbound logistics models. The paper proposes a customer interface network model, based on the CNO concept to tackle problems encountered.

Competitiveness and deregulation in the leather industry require new type cooperation among the supply chain members to increase the efficiency and profitability. The leather and leather products industry is a significant part of the developing countries’ economy. Even though the sector contributes a considerable amount of income, the sector has a lot of challenges that can be improved to increase value for the firms. The application of the model is gaining importance in the current literature. The application of the model facilitates the mapping of business processes for better understanding the supply chain members. In this paper, the adapted SCOR model is applied to the leather industry to find processes with higher pains to further improve Ethiopian leather industry. Semi-structured interview and industrial visits have been employed as research methods. The case study has demonstrated how the firms in developing countries can be benefited with application of the SCOR.

A lack of spare parts and ineffective maintenance lead to low service levels and high production costs. Intelligent maintenance systems (IMS) have been intensively considered for supporting a better performance of maintenance service. For achieving high supply chain performance, it is also necessary that the information provided by IMS is integrated into the operational planning of the spare parts supply chain. Thus, this paper proposes a procedure for the integration of the spare parts supply chain operational decision level and the IMS. A framework comprising a heuristic approach along with a simulation model and a mathematical model is proposed.

In this paper, the interlink between the concept of macro-institutional complexity in logistics and the dynamics in the logistics practice of Eastern Europe will be examined. Referring to the importance of different authors having ascribed to the external environmental uncertainty on organizational structure and transactional costs, the concept of environmental complexity is applied to the logistics management perspective. Thereby, the impacts which a given framework on a macro-institutional level might have on the situation and leeway in decision-making at the firm (micro) or the supply chain (meso) levels will be analysed. Furthermore, a quantitative modelling approach will be presented and exemplified by using the case of logistics infrastructure in Eastern Europe.

A container port is a crucial interface between the maritime and the hinterland transportation. In order to improve this interface, joint efforts between truck companies and a port terminal operator are necessary. However, a port terminal operator should transfer containers onto inland trucks responding to unexpected arrivals of them. It causes that handling equipment often have to relocate containers in order to pick up a desired one under them. These container-rehandling operations result in the waste of energy and the long waiting of inland trucks with greenhouse gas emissions. This paper addresses the inbound carry-out process for empty containers where a port terminal operator carries out them onto inland trucks at a port. The objective of this paper is to reduce the number of container-rehandles during this process, which leads to decrease in waiting time for inland trucks and increase in productivity of handling equipment. This paper applies the policy of the category stacking to the inbound containers. According to the predefined categories of containers, a port terminal operator is able to stack containers on the top of those in the same category. Truck companies can issue pickup orders of empty containers by specifying only the category instead of specifying container numbers. Based on this strategy, this paper proposes a collaborative process between a port terminal operator and truck companies. Simulation experiments are done to validate the strategy in this paper.

This paper proposed the double optimization objectives including minimization of total transport cost and total transport time in container multimodal transport from the perspective of multimodal transport operators. Based on the routes selection and convergent combination of transport time, space, and volume, an optimization model of segmented procurement in container multimodal transport was established with regard to the elements constraints of shippers’ orders, organization forms of container multimodal transport, container delivery location, transportation road and mode, transportation time, and freight rate. The natural constraint language (NCL) was employed to establish algorithm procedure for searching and solving the problem. Numerical examples show that the model and its searching algorithm are not only prone to implement and solve the problem, but also are quite good at the application results, and the goal of seamless integrated container multimodal transport is achieved.

E-Mobility is a hot topic, in the public policy area as well as in business and scientific communities. Literature on electric freight transport is still relatively scarce. Urban freight transport is considered as one of the most promising fields of application of vehicle electrification, and there are on-going demonstration projects. This paper will discuss case study examples of electric freight vehicle initiatives in Denmark, Germany, the Netherlands, Sweden and the UK and identify enablers and barriers for common trends.

The purpose of this study was to improve multimodal transportation strategy by evaluating and analyzing demand on roadway, railway, marine, and air transportation while investigating and collecting data on the southern supply for transportation with in depth interviewing for problems and ways to manage multimodal transportation in the South. From this research, the researcher developed a costing template for multimodal transportation between road and water transportation modes, covering all of the related activities on road transportation, port operation, and marine transportation activities. Moreover, the researcher also developed a “MULTIPLE” strategy which would apply to multimodal transport management between the roadway and marine transportation mode of containerized transporters in order to achieve the highest transportation efficiency and benefits.

In response to climate regulations and customers’ requirements, companies are now realizing that they will have to pay for their emissions under business as usual strategies. Emission trading scheme (ETS) was adopted and is going to take great effect in the way of cutting emissions. Hence, supply chain is faced with new challenges toward a sustainable business development. How to optimize the supply chain across all its stages to minimize their carbon footprint under ETS builds the main topic of this dissertation. The impact of ETS on sustainable development of supply chain is going to be analyzed at first and a supply chain-ETS is proposed to be implemented as a trial to test how companies along supply chain cooperate with each other based on common resource collaboration management.

Competition is no longer based on just bare company versus company business models, but supply chain versus supply chain. These create opportunities for the development of different supply chain models, such as the supply chain operations reference (SCOR) model. However, the existing models have not considered the early parts of the raw material suppliers’ situations in the firms of developing countries (DC). In addition, the supply chain in DC has unique challenges. The successful model is delayed by these challenges. In order to incorporate the DC situation, it requires examining the firms supply chain characteristics in the DC. A questionnaires survey and semi-structured interview questions are used to collect the current practices. Based on the survey results analysis, we have identified the supply chain characteristics. These characteristics help to define the new requirements. This paper presents the proposed changes related to the deliver and source processes. Future work will consider the adaptation of the entire model.

Dynamic systems such as global supply chains (SC) compel the workforce of all involved players to be faced with ever-changing working environments. This complexity makes it difficult to predict the impact of decisions taken, thus future SC managers need to be trained in taking decisions under uncertainty and to reflect the impact on the whole SC. This type of practical decision making is necessary to take shape within the business and engineering schools since it prepares future practitioners for the requirements they will face. Game-based learning (GBL) is well suited to GBL process. This paper compares two different game-based learning setups with students. The first explains a pure game-based course, whereas the other discusses how a new game is introduced in an undergraduate course on container security. Our comparison helps others to avoid pitfalls in the introduction of GBL in logistics education.

Innovation within companies is a collaborative process. Supply chain management (SCM) concepts such as ‘Early Supplier Involvement’ and ‘Open Innovation’ encourage the involvement of stakeholders, such as suppliers, customers, universities and the government. Customer participation for example helps to reduce the uncertainty of acceptance of an innovation in advance. Following market launch, the number of stakeholders increases further. With investors, customers and competitors globally dispersed, the stakeholder network of a new innovation could become complex and unmanageable. This not only makes risk identification arising from innovations very complex but also the accompanying assignment of responsibility. Research on Responsible Innovation (RI) brings along various challenges that arise from the rights, duties and behavior of stakeholders. This paper aims to identify the most important stakeholders for Responsible Innovations and determine their influence on the innovation lifecycle using the car development process as an example.

By surveying university educators across the world who teach logistics [and supply chain management (SCM)], this paper sought to gauge key opinions and issues both now and in the future regarding how the subject is taught. Specifically, we identify both the most effective teaching methods currently used and those that logistics academics would like to use to impart knowledge to students. Responses were collected and analyzed from 17 countries via an anonymous questionnaire. Of the current teaching methods, case studies and in-class discussion emerged as the most used. In terms of future teaching methods that academics would like to use, simulations featured prominently as did the increased use of virtual-based teaching. The paper closes with a future research agenda including garnering opinion from other stakeholders such as industry executives and students as well as focusing on the likely implications of the increasing use of virtual classrooms.

Usually, production and supply networks are characterized by insufficient transports, where resources are not fully utilized, delivery time performance and service level can be improved. Existing IT-systems do not support a holistic planning of transports considering all participants and their available resources. However, especially in supply chains, an integrated planning of transport resources is essential. Participants, e.g., transport service providers require the same resources like cranes at loading points. In this paper, a concept for an integrated transport management system is introduced supporting the long- and short-term demand-capacity planning as well as the execution phase.

Partner selection is one of the first steps in establishing partnerships. Traditional supply chain partner selection models assume that a buyer searches for one or more suppliers from a set of suppliers. Once the best supplier is found and selected, a partnership is formed. However, in reality, the relationship itself is bilateral, and the existence of other buyers and suppliers needs to be taken into account. In this paper, an interactive partner selection approach is proposed, where not only the buyers evaluate suppliers, but also the suppliers have the opportunity to evaluate buyers. Considering a marketplace where there are several buyers and suppliers, an integrative model is proposed in the form of an assignment model to optimally match all the buyers and suppliers. The proposed model is illustrated using a numerical example.

The durability of perishable food varies due to different storage and handling conditions during the supply chain as well as final consumer activities. If the durability of the individual products can be estimated, dynamic expiry dates may be developed and used to prevent food waste, ensure quality, and improve supply chain activities etc. Depending on the system architecture used for such a service, different qualities can be obtained in terms of usability, accuracy, security etc. This paper presents a novel approach for how to identify and select the most suitable system architectures of a dynamic expiry date service. The approach is illustrated by focusing on one of the potential user groups, the supply chain managers. The approach consists of three steps: (i) identify the potential architectures, (ii) filter out the least relevant candidates by applying a specified set of principles, and (iii) perform an analytic hierarchy process (AHP) based on a set of quality attributes.

Innovation has historically played a vital role in increasing efficiency. However, while other industry sectors have experienced rapid growth of productivity, the transport logistics industry has seen relatively small improvement in terms of efficiency. The European LOGINN project undertakes several activities aiming at fostering collaboration among the involved stakeholders of the logistics domain regarding the promotion of innovative transport logistics solutions. The LOGINN approach for supporting logistics innovation achievement involves three interlinked and mutually reinforcing dimensions: innovative business models within the supply chain, innovative logistics best practices, and innovative technologies. In this work, we describe a methodology for innovative best practices identification and we present a selection of best practices identified from the LOGINN project in the areas of e-freight, co-modality, urban freight distribution, and intralogistics.

Learning factories and laboratories are a great enrichment for university education and training. Many universities worldwide use laboratories to support the education. Especially the logistics area is highly qualified to be supported by laboratory-enriched education. This paper highlights some trends in didactics and the benefits of laboratories on the example of a logistics laboratory at the Chair of Industrial Logistics.

Automobile industry like many other industries is rapidly moving toward mass customization. However, the phenomena of mass customization did not prove to be fruitful for all the companies that adopted it. Success of this mass customization depends upon supply chain management along with proper strategies. There is no proper model for automobile industry yet that explains the optimal level or extent to which different strategies should be applied with proper supply chain. This study will try to bring out this gap by doing the case study of leading German mass customized automobile companies.

Global business opportunities require companies to work with suppliers and customers worldwide. The supply chain management (SCM) assumes increasing significance for the world community, at the same time there is competition not between companies but global supply networks, which are increasingly replacing supply chains. As a result, competition between companies in global markets increasingly means competition between networks; however with globalization, corporate planning has turned out to be under the strong influence of distribution networks, in the focus of attention of which is not a product but customers’ value. This article considers the logistics systems from the point of view of conveying value by means of supply networks decentralized control systems and centralized adoption of global networks.

Logistics is an important business sector for the German economy. But it is influenced by so-called social and economic megatrends that lead to rising qualification and competence requirements. In this context it could be asked, if existing qualification and competence profiles do fit these quickly rising new requirements. This extended abstract discusses first approaches and attempts to find out, if misfits between new qualification and competence requirements and existing qualification and competence profiles indeed exist. Furthermore, first ideas of follow-up problems for employees and human resource managers in logistics are sketched.

Demand forecasting of fashion apparel products has to cope with serious difficulties in order to get more accurate forecasts early enough to influence production decisions. Demand has to be anticipated at an early date due to long production lead times. Due to the absence of historical sales data for new products, standard statistical forecasting methods, like, e.g., regression, cannot easily be applied. This contribution applies selected methods into improve forecasting customer demand of fashion or seasonal apparel products. We propose a model which uses retailer pre-orders of seasonal apparel articles before the start of their production to estimate later, additional post-orders of the same articles during the actual sales periods. This allows forecasting of total customer demand based on the pre-orders. The results show that under certain circumstances it is possible to find correlations between the pre-orders and post-orders of those articles, and thus better estimate total demand. The model contributes to the improvement of production volumes of apparel articles, and thus can help reduce article stock-outs or unwanted surpluses.

The purpose of this paper is to describe a multiple criteria benchmarking and monitoring system for assessing the performance of industrial sectors. The referred system was designed for comparing and monitoring companies’ performance against market requirements. As an illustration, data collected during a three-year period for a specific local productive arrangement of Ceará, Brazil are showcased. The findings indicate the opportunities and needs for collective strategic actions by the companies and sectors in order to promote local development.

This paper deals with the modeling, routing, and managing aspects of a warehouse with parallel aisles and cross-aisles, in which we assume a picker-to-part process. Pickers either retrieve in the aisles-stored products to fulfill a customer order, or do some nonurgent activity. The main contribution of this paper is the consideration of constraints, which are often disregarded by other papers. We study in particular the consequences of some ‘working conditions’ for the pickers on the overall solution quality. We analyze a warehouse layout designated to vehicle routing. We study the organization of products into locations, given some statistical forecasts on the future orders. Then we describe a management strategy to regulate the number of pickers doing the picking activity. Finally, an algorithm is proposed as a solution and tested by simulation experiments.

Product and process innovations are viewed as a key factor for the competitiveness of organizations and regions and for achieving economic growth. The efforts of researchers in this area are focused on identifying good practices, related to the management of new products development (NPD), and bringing out those with high success rate. A number of studies on the NPD process prove that the increased research and development activeness (R&D) increases the comparative advantages and is the basis for market approval of industrial enterprises-innovators. This determines the interest of authors in studying the area of efficient management of the NPD process in industry. They research practices applied in Bulgarian industrial enterprises with the aim to prove the significance of the technology and organization for NPD and use it to synthesize and summarize a set of specific quality parameters for improving the management functions, applicable in medium-sized and large enterprises for the processing industry in approving their performance, compared to the competitors in the sector concerned.

Entering emerging markets (EMs) is a huge opportunity and a risk for small and medium-sized enterprises (SMEs). This paper concentrates on the problems emerging from building a supply network in a target economic area. Cultural, legislative, and market factors make it a challenge, but SMEs also face diverse obstacles from side effects emerging from firm’s internal decisions. Some of these obstacles are self-generated, and they arise from aggressive growth strategies in parallel with misunderstanding the dynamics of one’s own firm—the unintended consequences of decisions. In this paper we will analyze the internal restrictions on Finnish SMEs or actions impeding or accelerating their growth in EMs. A conceptual system dynamics model is constructed so as to describe the challenges of entering EMs. The model is based on a literature review, VTT logistics experts, and interviews conducted with Finnish SMEs.

We analyzed the urban logistics problems in Istanbul City, and we tried to show the solutions of these problems thanks to intermodal freight terminals. Istanbul is a center of trade, tourism, and industry; 60 % of total logistics activities take place in Istanbul. At the same time, capacities, infrastructures, and performance of logistics system are affecting the logistics systems and industries of European countries and neighborhoods. However, solving the urban logistics problems have become regional and global ones and especially European countries, industries, and their commercial actors cannot ignore these problems. In addition to urban freight flows, high volume of international and domestic cargo flows causes different problems related to urban logistics. On the other hand, Istanbul has the different logistics nodes as airports, organized industrial zones, business centers, whereas logistics networks and links between nodes are not required level. This study focuses on the logistics nodes, relationships, opportunities and facilities of transportation, and effects of intermodal freight terminals to solving problems of the insufficient connections between these nodes.

The project performance monitoring tools are not only for insuring the success of the project, but they also provide the proper input for manager decision making process. It is very difficult to find such a comprehensive and complete method which has high accuracy to rendering performance information of a given project. However, research has shown that without a prospective strategic outlook on project organization, the chance of success of a given project is reduced. This article introduces a project balance evaluation (PBE) method as a new approach to project monitoring. This method uses a modified version of the Balanced Score Card (BSC) tool and the earning value method (EVM), to evaluate project performance. With this modification, PBE acts as a useful tool for project performance management.

This paper presents a framework using analytical equations and simulation to choose the best material flow control system based on inventory cost and starvation performance. The study concentrates on in-plant milk run system and compares between traditional material flow control systems such as push and traditional kanban; and a new and more dynamic system which is an electronic kanban. A new electronic kanban system, called adjusted electronic kanban (AEK) that can utilize RFID technology has been proposed to deal with milk run trains shortages to decrease starvation of assembly lines. Simulation results showed that push system is effective when the variability in material consumption is not so high. Moreover, regular kanban is effective if there is sufficient trains’ capacity, but electronic kanban gives lower inventory levels. In the case of severe trains’ capacity shortages, AEK was found to be the best alternative.

The subject of the report is substantiation of the definition “Destination” in terms of pseudo-touristic space and the use of the coordinate model, the equilibrium model of the center of mass, the method of the optimization of the objective function, and the method of relative preference to define the expected (cost-effective) geographical location of the tourist center with distinctive meanings of “heritage.”

The fashion industry faces different challenges in the field of demand forecasting. Factors such as long delivery times in contrast to short selling periods requires precise demand figures in order to place accurate production plans. This paper presents firstly the idiosyncrasies of the fashion industry and shows current fashion forecasting approaches. Then, the idea of applying social media text data within the demand forecasting process is presented by showing works of integrating user generated content in different application fields. Following the research question on the predictive value of social media text data for the fashion industry, the research objective and the methodology are formulated in a last step.