Logistics Management

Delays or cancellations of flights are mostly caused by avoidable, maintenance-related downtime of aircrafts. For a more efficient supply of spare parts for aircrafts of an airline, we examine options for improving the underlying logistics network integrated within an existing segment of the aviation industry. The objective is to guarantee a high supply of spare parts. Moreover, the paper presents effects of the choice of different maintenance strategies on total maintenance costs. By applying a condition-based maintenance strategy, unscheduled component failures can be reduced and an increase in availability and reliability is possible. A validation of the developed model is provided by means of a simulation study.

The consideration of Small and Medium-Sized Enterprises (SMEs) in tender processes is an important goal of public procurement regulation. Public procurement law sets the rule to divide contracts in smaller lots as SMEs are expected to have better chances for a lot than for the whole task. This assumption is questioned with data from the German defence sector. This investigation determines the percentages of SMEs participating in and winning public tenders as well as the specific factors that influence award decisions. Key finding is that an increase in lot-wise calls will normally not lead to an increase in successful SME participation in public procurement processes. This is unexpected because lot-wise tenders are considered to be the main tool available to public procurement agents to increase the ability of SMEs to participate in and win public tenders.

In international sourcing and in strategic partnerships cultural differences can lead to problems in the cooperation of buyer and supplier. Therefore, cultural criteria should be included in supplier evaluation and selection processes in order to anticipate and to avoid possible problems. Although there are recommended cultural criteria in literature, we do not know much about the application of cultural criteria in supplier evaluation. In this paper, we present the results of an empirical study about the integration of cultural aspects in supplier evaluation. We explore company practices and problems with suppliers due to cultural differences. Furthermore, we give recommendations for the application of cultural criteria in supplier evaluation processes in practice.

Planning in supply chains is characterized by uncertainties. These can be disruptive as well as operational risks, but also business opportunities. To deal with uncertainties, various approaches suggest supply chains that are robust, resilient, and agile (RoRA). To accomplish this, flexibility is necessary. Aspects of flexibility in supply chain management (SCM) have been analyzed from different angles. But still a holistic concept on how flexibility planning can be integrated in the process of supply chain planning does not exist. This paper gives an overview on optimization models used for flexibility planning in supply chains and identifies the characteristics of such a planning process. Which tasks of SCM the components of flexibility planning have to be integrated in is discussed along the structure of the supply chain planning matrix. An outlook on further research on flexibility planning in RoRA-SCM is also given.

The more efficient configuration and coordination of multimodal transports is a topic consistently emerging in the last decades. Different projects, like e.g. LOGFOR, CODE24 and CENTRAL EUROPE, make efforts to achieve progress in this area. In this paper an already implemented and tested software prototype for the configuration of multimodal supply chains is presented. It is described how this prototype, which emerged from the CODE24 project, is able to facilitate contact between potential business partners. Subsequently, the paper shows how the implementation of the prototype and the research into freight exchanges led the authors of this paper to a new marketplace concept: Agent-based Freight Exchanges. These yet to be implemented, highly automated and interconnected marketplaces are designed to address problems commonly associated with existing intermediaries. They will provide support for decentralized and autonomous software agents to perform contractually binding auctions of multimodal freight transport services. It is also shown how the agents will utilize a double-sided combinatorial auction model to achieve this. Finally, an outlook on prospective concepts which support the negotiation of contracts for multimodal transport services using multi-agent systems is given.

In 3PL relationships, complex, customised services are provided based on multi-year contracts. As practice reveals, contract design poses a major challenge to 3PL providers and clients. Contracts need to enable handling of changing requirements and contingencies that arise during contract terms. Contracts are designed flexible utilising specific flexibility mechanisms. These flexibility mechanisms reveal strengths and weaknesses depending on relationship characteristics. Inappropriate contracts provoke dissatisfaction, contract terminations, and transaction costs. The paper describes the use, strengths and weaknesses of flexibility mechanisms in 3PL contracts drawing on theoretical and practical analyses. Based on theory and practice, propositions and needs of further research are outlined.

An efficient layout arrangement and its aisle structure are particularly important due to material handling costs, which directly affect product costs. Traditionally this is a procedure of sequential steps. In recent literature there exist a few approaches to handle layout arrangement and aisle structure simultaneously using heuristics. Only one approach could be found to solve it exactly, but with a lack of exactness due to its discrete representation. In this article, a mixed integer programing model (MIP) is proposed to achieve an arrangement of equipment with fixed shapes, input/output points, and aisle structure with predefined widths simultaneously and exactly. Furthermore, a continuous representation is considered. For that purpose the MIP model of Kim and Kim (2000) is modified to reduce computing time and is enhanced later on to consider aisles. The applicability is demonstrated by a small computational test.

In this paper the network design, the capacity and production planning of a closed-loop supply chain (CLSC) with multiple make-to-order (MTO) products consisting of common components is studied. The components can be remanufactured or can be purchased new from suppliers. It is assumed that products are returned by customers to the same facilities where the final products are sold. Transportation between facilities of the same type, i.e. redistribution, is allowed. The network is explored over multiple time periods. The objective of this work is to extend the strategic CLSC management by integrating decisions regarding production planning on an aggregate level to achieve an integrated optimization of facility locations, capacity equipment and production quantities at the facilities and forward and reverse material flows. For this purpose a mixed-integer linear optimization model is developed and solved for an example set of data.

Layout decisions represent an important step in production planning as they significantly affect the efficiency of a facility. They typically follow after make-or-buy decisions and capacity planning of a firm, and belong to the lowest level in the hierarchy of tactical production decisions. Sequential decision making neglects however the potential interaction between consecutive planning levels and may lead to inefficiencies. We propose an approach to a simultaneous make-or-buy decision making and facility layout planning in the presence of multiple products. To this end, we introduce a generalization of the classical quadratic assignment problem that takes into account (i) the costs of outsourcing, and (ii) the impact of layout decisions on the production costs of individual products. We further propose a solution approach based on the linearization of the resulting model and derive basic properties of the optimal planning decisions.

Qualification and competence requirements in logistics companies are influenced by internal and external processes of change. To stay competitive and reactive to the market, those companies have to face the problem of qualification and competence related misfits. This paper presents a mixed method approach to identify and measure qualification and competence related misfits in different occupational groups and closes a gap in the literature. The use of the tool could provide valuable information to the HR development function of a logistics company.

Re-entrant scheduling problems are characterized by a multiple processing of the jobs on one or more machines. Such problems occur in wafer manufacturing, paint shops and rework operations. This paper proposes a lot streaming formulation for a re-entrant flow shop scheduling problem with missing operations. The examined objective values are makespan and the sum of completion times. The model is compared to an existing approach. In addition the impact of an increasing number of sublots is examined.

Identifying complexity-inducing factors is an essential precondition for the successful management of manufacturing complexity. However, established methods do not fully address the characteristics of semiconductor front-end manufacturing. This paper introduces Multiple Workflow Alignment (MWA) as a new approach to identify differences between products that increase semiconductor manufacturing complexity—so called complexity-inducing variety. MWA is an adaption of the biological sequence alignment algorithm ClustalW and is characterized by high accuracy and reliability. The resulting alignments can be used for logistic-oriented workflow-design and complexity measurement.

Highly automated manufacturing systems offer several advantages and are widely introduced as a strategy to improve the performance of manufacturing organizations. Various forms of automated equipment, such as industrial robots or flexible automatic machines, are used extensively in high-volume industrial production. Especially for flow production systems automation has advanced considerably. This type of production system can, for instance, be found in the automotive, home appliance, or electronics industry where highly automated flow lines are mainly implemented for safety, quality, and productivity reasons. A significant challenge in the operation of highly automated assembly lines is the occurrence of equipment failures which impair the throughput rate. Therefore, buffer space is allocated between the stations of an assembly line in order to achieve a desired throughput rate in spite of equipment failures. However, the installation of buffer space requires considerable investments and also leads to an increase of the average work-in-process inventory in the line. A different approach to achieve a desired throughput rate despite equipment failures is a redundant configuration, in which downstream stations automatically take over the operations of failed stations in the event of failure. The throughput loss in these situations mainly depends on the level of redundancy designed into the system. We present an assembly line balancing model for automated assembly lines which maximizes the lines’ level of redundancy for a given number of stations. In a numerical analysis we demonstrate the effectiveness of the approach and show that a redundant configuration allows for significant reductions of required buffer sizes in flow lines with unreliable equipment for a given throughput rate.

Natural and man-made disasters often have devastating effects on the affected population and the economy. Optimization models for determining the locations of relief facilities and the amount of first-aid items to be stored before the occurrence of an emergency can help decisively to mitigate the impact of a disaster. As research interest in disaster management has grown significantly over the last decade, this paper reviews the state-of-the-art literature concerning prepositioning of relief items in conjunction with facility location decisions, taking the uncertain nature of a disaster into account. A classification of the respective modeling approaches and solution methods is provided to facilitate the identification of relevant research gaps. One of the main findings is the lack of efficient solution methods especially for large scale problems, although generating optimal solutions in a reasonable timeframe is crucial for the success of a relief operation. Based on the detected gaps, future research directions are suggested.

High return rates are a problem particularly concerning e-tailers. Often, these returns are considered to come back as good as new which enables an immediate resale. This assumption does not take into account that some consumers show a dishonest buying intention by returning items they have already used. For reasons of an improved operational planning it could be helpful to predict this kind of product returns. Therefore, we adapt and enhance already existing forecasting approaches to situations where the e-tailer matches consumer returns with their date of sale and furthermore, where the consumer has to register the return first. The so generated product-individual data are covered by developing three forecasting methods. It is examined under which circumstances the models show a satisfying accuracy and correspondent requirements that have to be met in this context are inferred. The overall premise is the practicability in order to ensure an uncomplicated application.

City logistic service providers often have to decide under uncertainty. In some cases, not all customers are known at the time of the decision, but may request service in the course of day. Here, anticipation of possible future requests in current decision making is mandatory to avoid ineffective decisions and to serve a high amount of requests within the service period. In this paper, we present a vehicle routing problem with stochastic customer requests. The objective is to maximize the number of served requests regarding a time limit. Decision points occur dynamically by arriving at a customer. To achieve anticipatory decisions, we define a rollout algorithm (RA) combined with sampling of future requests. Over a limited decision horizon, RA maximizes the immediate reward and the expected rewards-to-go explicitly considering every customer. Later rewards-to-go are estimated by sampling using a cheapest insertion greedy decision policy. We compare the RA with a value function approximation (VFA) benchmark heuristic. VFA allows long-term anticipation on the expense of only implicit customer consideration using key parameters. For instances, where explicit customer consideration is necessary, RA achieves a significantly higher solution quality than VFA.

In this paper, a real-world cost function for vehicle routing occurring in the distribution planning of a large German food retailing company is considered. In contrast to the widely used standard formulation introduced by Dantzig and Ramser (Manage Sci 6:80–91, 1959), the price structure is based on transport tariffs as the retailer cooperates with several freight carriers. The resulting costs depend on the products transported on a route as well as on the chosen itinerary and therefore, are not completely known in advance. For a deeper understanding, the cost function is formally modeled and afterwards illustrated by different examples. Besides, a detailed description of the underlying real-world issue is given and several problem variants of the Vehicle Routing Problem (VRP), like the VRP with Compartments or the VRP with Time Windows, are derived from the features of the issue. Due to the variety of variants, it can be classified as a member of a recent problem family called Rich VRP.

This paper extends the open vehicle routing problem (OVRP) by time windows, truck specific starting positions and a common delivery position. This extension is called reverse OVRP with time windows (ROVRPTW). The ROVRPTW occurs e.g. in dynamic vehicle routing problems, when at planning updates “return trips” to a central depot have to be generated. For generating cost-efficient transportation plans for the ROVRPTW, the well-known adaptive large neighborhood search (ALNS) is modified. A computational benchmark study is carried out, that compares the modified ALNS with other approaches for the vehicle routing problem with time windows and the OVRP, where also new best solutions are included. In addition, the algorithmic performance on the ROVRPTW is evaluated by solving a set of generated instances.

The Inland Container Transportation Problem defines the movement of fully loaded and empty containers among terminals, depots, and customers within the same inland area. All kinds of customer requests are organized by one trucking company that owns depots containing a homogeneous fleet of trucks and a sufficiently large set of empty containers. The objective of this study is to minimize the total distance the trucks travel. We present a two-stage iterative solution approach that is capable to optimize around 300 requests. In the first step, the set of requests is divided into subsets, a tabu list prevents returns to recently considered subsets. In the second step, a mathematical problem is solved for each subset. These steps are then repeated and the best known solution is updated so long as certain stopping criteria are not met. The approach is implemented in C++ using IBM ILOG CPLEX. The quality was verified by several computational experiments.

We present a distributed decision making approach for the problem of combined vehicle routing and break scheduling. This problem consists of finding vehicle routes to service a set of customers such that a cost criterion is minimized and legal rules on driving and working hours are observed. In the literature, this problem is mostly analyzed from a central planning perspective. In practice, however, this problem is usually solved coactively by planners and drivers. One possible distribution of tasks is such that the planner does the clustering and routing of the customer requests and instructs the drivers which customers they have to visit in which order. Subsequently, the drivers decide upon their break schedules. We apply a framework for distributed decision making to model this planning scenario and propose various ways for planners to anticipate the process of tour fulfillment performed by the drivers. We analyze whether the way of anticipation has direct impact on the quality and usefulness of the plans representing the planner’s instructions for the drivers. Computational experiments performed on the planning situation of a single driver demonstrate that a high degree of anticipation by the planner has a positive impact on the overall planning process.