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The development of Operations Research (OR) requires constant improvements, such as the integration of research results with business applications and innovative educational practice. The full deployment and commercial exploitation of goods and services generally need the construction of strong synergies between educational institutions and businesses.

The IO2015 -XVII Congress of APDIO aims at strengthening the knowledge triangle in education, research and innovation, in order to maximize the contribution of OR for sustainable growth, the promoting of a knowledge-based economy, and the smart use of finite resources.

The IO2015-XVII Congress of APDIO is a privileged meeting point for the promotion and dissemination of OR and related disciplines, through the exchange of ideas among teachers, researchers, students , and professionals with different background, but all sharing a common desire that is the development of OR.



A Model to Minimize Costs and Promote Species Persistence under Climate Change

Biodiversity is severely threatened by the effects of changing climates that cause species to readjust their spatial ranges. But species are limited in their capacity to follow suitable climates, as these rearrange in space along time. Therefore, the identification of the areas to support spatial readjustments of species is a pivotal step that should be made thoroughly given the limited budgets available. We propose a two-stage mixed integer linear programming to formalize this issue, present a heuristic and report results comparing optimal and heuristic solutions.
Diogo Alagador, Jorge Orestes Cerdeira

A Fix-and-Relax Algorithm for Solving Parallel and Sequential Versions of a Multi-period Multi-product Closed Loop Supply Chain Design and Operation Planning Model

In this work we present the sequential and parallel versions of a heuristic algorithm for the solution of a two-stage stochastic mixed 0-1 model for closed loop supply chain planning problem along a time horizon. Some computational experience conducted on randomly generated networks shows the quality of the proposed approach.
Susana Baptista, Maria Isabel Gomes, Laureano Escudero, Pedro Medeiros, Filipe Cabrita

Efficiency in Increasing Returns of Scale Frontier

The main objective of this paper is to analyze DMUs efficiency from different perspectives of variable returns to scale. For that, the authors use results of CCR, BCC and a new model proposed. The new model presents just in-creasing returns to scale. Thus, the efficient frontier must have specifics characteristics that guarantees increasing additional output beyond additional inputs verified. This study is going to show that the classic model of DEA BCC proposes variable returns of scale, however cannot ensure that all the efficient DMUs with increasing returns to scale is identified. The authors propose a new model where the measurement of efficiency is made by increasing returns to scale frontier.
Juliana Benicio, João Carlos Soares de Mello, Lidia Angulo Meza

Modeling Inter-sector Health Policy Options and Health Gains in a Long-term Care Network: A Location-Allocation Stochastic Planning Approach

Although not a common practice, proper planning of health care networks should consider the attainment of health gains and the impact of inter-sector health policy options. This study proposes a multi-objective stochastic model to support location-allocation decisions in the long-term care sector that integrates these aspects. The model aims at maximizing expected health gains and minimizing expected costs, using the augmented (-constraint method for analyzing this trade-off. The impact of inter-sector policy options on this trade-off is explored. A case study in Portugal is analyzed.
Teresa Cardoso, Mónica Duarte Oliveira, Ana Paula Barbosa-Póvoa, Stefan Nickel

Optimization of Construction and Demolition Waste Management: Application to the Lisbon Metropolitan Area

This work presents a mixed integer linear programming (MILP) model of a construction and demolition waste (CDW) recycling network that includes a methodology for environmental impact assessment (Eco-indicator 99). Applied to a geographical area, this generic formulation can be used for feasibility studies and sensitivity analyses of the input parameters, while simultaneously defining the optimal network design, i.e., the location and capacity of the installed facilities and material flows. Furthermore, by using the ε-constraint methodology, the Pareto Front is drawn, allowing the decision maker to choose the solutions presenting the best tradeoff between economic and environmental goals.
The model was applied to a Lisbon Metropolitan Area case study, which required extensive data collection and estimation. Different instances of the problem were generated, by varying conditions and model parameters (sensitivity analysis), and the MILP model solved. Solutions comprise a small number of high capacity recycling plants, when cost minimization is at stake, while when preference is given to the minimization of environmental impacts solutions comprise several geographically dispersed recycling plants of low capacity.
Mafalda Neiva Correia, Marta Castilho Gomes, Joaquim Duque

Financial Structure, Product Market Decisions and Default Risk in an Asymmetric Duopoly

Financial and output market decisions are crucial to the success or failure of an organization. In this paper we analyze the equilibrium default risk in a two-stage duopoly model with an uncertain environment, where firms decide their financial structure in the first stage of the game and decide their quantities in the second stage of the game. Using numerical analysis, we analyze the impact of changing the asymmetry in the two firms’ marginal costs on the equilibrium default risk. Our results show that as a firm becomes less efficient it is optimal to reduce its debt level and the quantity produced. The reverse is true for the more efficient firm. This behavior implies that although higher marginal cost leads to lower profits, the less efficient firm reduces its default probability due to a more cautious behavior in the financial and product market.
Magali Costa, Cesaltina Pacheco Pires

On the Optimization of Aircraft Maintenance Management

Task scheduling and resource allocation problems have been the subject of intense research over the past decades, particularly within Operations Research. However, seldom optimization models have been proposed to address the aircraft maintenance management process in an integrated manner. Besides eliciting the problems of capacity planning, parts forecasting and inventory management, and task scheduling and resource allocation faced by aircraft MRO companies, this paper presents a short review on models that address each of the problems and discusses research opportunities within this field.
Duarte Dinis, Ana Paula Barbosa-Póvoa

Petroleum Supply Chain Network Design and Tactical Planning with Demand Uncertainty

The energy sector has dominated the world attention as recently arrived shale gas and slumping crude oil prices globally affect Petroleum Supply Chains (PSC). Fluctuating demand and prices are forcing companies to rethink existing distribution networks and production plans in order to improve network flexibility and cost efficiency. The current paper addresses this problem and presents a stochastic mixed integer linear program (MILP) for PSC design and planning under demand uncertainty that maximizes the expected net present value (ENPV) of a multi-entity multi-product PSC network. The decisions include locations, capacities, transport modes, routes, product affectations, inventories and fair-price costs and tariffs with economies of scale. The stochastic MILP designs a grassroots network with demand uncertainty for the Portuguese PSC, drawing important insights and research directions.
Leão José Fernandes, Susana Relvas, Ana Paula Barbosa-Póvoa

Modeling Lot Sizing and Scheduling in Practice

Lot sizing and scheduling by mixed integer programming has been a hot research topic in the last 20 years. Researchers have been trying to develop stronger formulations, as well as to incorporate real-world requirements from different applications. In this paper we illustrate some of these requirements and show howmodels have been adapted and extended. Motivation comes from different industries, especially from process and fast moving consumer goods industries.
Luis Guimarães, Gonçalo Figueira, Pedro Amorim, Bernardo Almada-Lobo

Improving the Robustness of Bus Schedules Using an Optimization Model

This study pursues the operational improvement of urban transportation services. Non-foreseen events lead to the occurrence of delays, which are further propagated during the daily operations of bus services. This paper applies an optimization model to obtain robust schedules of bus lines. The model builds a new schedule which minimizes delays and anticipations from a set of observations. The decision variables are the slack time to be allocated at each segment of two subsequent stops. The solutions obtained are assessed with two robustness measures: price of robustness (i.e. the deviations from schedule) and the percentage of absorbed delays. The results obtained in a real-world case study (a bus line operating in Porto) are promising.
Joana Hora, Teresa Galvão Dias, Ana Camanho

Airport Ground Movement

Worldwide air traffic tends to increase and for many airports it is no longer an option to expand terminals and runways, so airports are trying to maximize their operational efficiency. Many airports already operate near their maximal capacity. Peak hours imply operational bottlenecks and cause chained delays across flights impacting passengers, airlines and airports. Therefore there is a need for the optimization of the ground movements at the airports. The ground movement problem consists of routing the departing planes from the gate to the runway for takeoff, and the arriving planes from the runway to the gate, and to schedule their movements. The main goal is to minimize the time spent by the planes during their ground movements while respecting all the rules established by the Advanced Surface Movement, Guidance and Control Systems of the International Civil Aviation. Each aircraft event (arrival or departing authorization) generates a new environment and therefore a new instance of the Ground Movement Problem. The optimization approach proposed is based on an Iterated Local Search and provides a fast heuristic solution for each real-time event generated instance granting all safety regulations. Preliminary computational results are reported for real data comparing the heuristic solutions with the solutions obtained using a mixed-integer programming approach.
Miriam Lobato, Filipe Carvalho, Ana Sofia Pereira, Agostinho Agra

Optimization of a Recyclable Waste Collection System - The Valorsul Case Study

This paper studies alternative scenarios for a recyclable waste collection system in order to increase efficiency in their operations. Three alternative scenarios are proposed where two different locations for one or two additional depots are studied. The problem is considered as a multi-depot vehicle routing problem and a solution approach is developed. The three scenarios are compared with the current solution regarding distance travelled, working hours, amount of waste collected and vehicle usage. Significant gains are obtained when depots are added to the current logistics system.
Diogo Lopes, Tânia Rodrigues Pereira Ramos, Ana Paula Barbosa-Póvoa

Simulated Annealing for Production Scheduling: A Case Study

In this work, a production scheduling problem is developed through a Simulated Annealing approach, with the Tardiness minimization as objective function. The algorithm is applied to a plastic container facility, which operates an injection molding process with several parallel machines. The algorithm applicability and its performance is illustrated through two production strategies, the make-to-order (MTO) and make-to-stock (MTS). In the latter inventory management is taken into account.
António Santos Marques, Nelson Chibeles-Martins, Tânia Pinto-Varela

Applying Superquantile Regression to a Real-World Problem: Submariners Effort Index Analysis

We lay out the fundamental theory for superquantile regression. Such novel regression framework is centered on a coherent and averse measure of risk, the superquantile (also called conditional value-at-risk), which yields more conservatively fitted curves than classical least squares and quantile regressions. We illustrate this regression technique by analyzing a real-world problem where a random variable represents the effort index of the Portuguese Navy submariners along their Navy careers. This index was created as a decision tool to support human resource management inside the Submarine Squadron.
Sofia Isabel Miranda

Recent Trends and Challenges in Planning and Scheduling of Chemical-Pharmaceutical Plants

This paper discusses the current trends in optimization methods for solving planning and scheduling problems in the chemical-pharmaceutical industry. The challenges of this industry and the recent advances in modeling these problems show that optimization methods need to provide highly integrated solutions encompassing decision-making at both R&D and Operations levels. The heterogeneous demand, characteristic of the complex drug development cycle, asks for mixed planning strategies capable of increasing the resources utilization and the plant output, and of dealing with uncertainty.
Samuel Moniz, Ana Paula Barbosa-Póvoa, Jorge Pinho de Sousa

Planning Collection Routes with Multi-compartment Vehicles

This paper aims to assess the impact of using vehicles with multiple compartments in a recyclable waste collection system. Such systems perform single-material routes to collect three types of recyclable materials (paper, glass and plastic/metal), where vehicles with a single compartment are used. If vehicles with multi-compartments were used, two or even the three materials could be collected simultaneously without mixing them. A heuristic approach is developed to solve the multi-compartment vehicle routing problem and applied to a real waste collection system operating in Portugal.
Adriano Dinis Oliveira, Tânia Rodrigues Pereira Ramos, Ana Lúcia Martins

Pricing for Internet Sales Channels in Car Rentals

Internet sales channels, especially e-brokers that compare prices in the market, have a major impact on car rentals. As costs are heavily correlated with unoccupied fleet, occupation considerations should be integrated with swift responses to the market prices. This work was developed alongside Guerin, a Portuguese car rental, to build a tool that quickly updates prices on e-brokers websites to increase total value. This paper describes the specificities of the problem and their implication on the solution, and presents an adaptative heuristic to update prices and the system’s architecture.
Beatriz Brito Oliveira, Maria Antónia Carravilla, José Fernando Oliveira, Paula Raicar, Delfina Acácio, José Ferreira, Paulo Araújo

Eco-efficiency Assessment at Firm Level: An Application to the Mining Sector

Assessing firms’ Eco-efficiency is important to ensure they succeed in creating wealth without compromising the needs of future generations. This work aims to extend the Eco-efficiency concept by including in the assessment new features related to environmental benefits. Eco-efficiency is evaluated using a DEA model specified with a Directional Distance Function. The new methodology proposed in this paper is illustrated with an application to world-class mining companies, whose results and managerial implications are discussed.
Renata Oliveira, Ana Camanho, Andreia Zanella

Exploring a Column Generation Approach for a Routing Problem with Sequential Packing Constraints

In this work we propose a computational study of a column generation based heuristic prototype for the vehicle routing problem with two-dimensional loading constraints. This prototype was recently proposed in literature (Pinto et al., 2013) and it relies in a column generation algorithm whose subproblem is relaxed. After solving the subproblem, the feasibility of the routes is verified using lower bounds and the classical bottom-left heuristic, enhanced with sequential constraints. For the infeasible routes, a simple route shortening process is applied, and the feasibility is tested again. The effectiveness of our approach is evaluated using benchmark instances from the literature.
Telmo Pinto, Cláudio Alves, José Valério de Carvalho

Design of Retail Backroom Storage: A Research Opportunity?

The design of retail backroom storage has a great impact on in-store operations, customer service levels and store life-cycle costs. Moreover, backroom storage in modern retail stores is crucial to several functions, such as acting as a buffer against strong demand lifts yielded by an increasing promotional activity, seasonal peak demand and e-commerce activities. Despite having similar functions to a distribution center, backroom storage facilities have particularities that deserve a distinct analysis. In this paper we aim to draw attention to the lack of research about this topic.
Maria Pires, Pedro Amorim, Jorge Liz, Joaquim Pratas

The Suppliers Selection Problem: A Case Study

The effective supplier evaluation and purchasing processes are of vital importance to business organizations, making the suppliers selection problem a fundamental key issue to their success. We consider a complex supplier selection problem with multiple products where minimum package quantities, minimum order values related to delivery costs, and discounted pricing schemes are taken into account. Our main contribution is to present a mixed integer linear programming (MILP) model for this supplier selection problem. The model is used to solve several examples including three real case studies from an electronic equipment assembly company.
Mariana Costa, Cristina Requejo, Filipe Rodrigues

An Integrated Decision Support System to Assess the Sustainability of Demand Responsive Transport Systems

The provision of conventional public passenger transport services in rural areas have shown to be very inefficient and ineffective due to low levels of population density and high spatial and temporal dispersion. Demand Responsive Transport (DRT) systems have been seen as an interesting alternative solution, adopted in several countries as a way to increase user’s mobility, providing flexible transport services to meet trip requests and mitigate social exclusion. However, some DRT systems have revealed to be inadequate or even unsustainable, mainly because they are highly dependent on the correct tuning of organizational and functional parameters, namely the level of flexibility of schedules, routes and stop locations. Despite the existence of a vast literature concerning DRT systems, very few contributions have been put forward concerning comprehensive approaches to tackle these problems and to assess sustainability. This paper proposes a new integrated multi-disciplinary decision support system (DSS) to help decision-makers design and plan DRT systems, and assess their sustainability. The proposed DSS comprises analytical and simulation tools and consists of a procedure that iteratively simulates and evaluates alternative specifications of the system until an adequate and sustainable solution is encountered. The new tool has been applied to a case study in a rural area of the northwest of Portugal, and preliminary results suggest that the proposed approach was able to identify a set of conditions under which a DRT system can be sustainable.
Ana Cecília Ribeiro, Maria Sameiro Carvalho, José Telhada

GPU-Based Computing for Nesting Problems: The Importance of Sequences in Static Selection Approaches

In this paper, we address the irregular strip packing problem (or nesting problem) where irregular shapes have to be placed on strips representing a piece of material whose width is constant and length is virtually unlimited. We explore a constructive heuristic that relies on the use of graphical processing units to accelerate the computation of different geometrical operations. The heuristic relies on static selection processes, which assume that a sequence of pieces to be placed is defined a priori. Here, the emphasis is put on the analysis of the impact of these sequences on the global performance of the solution algorithm. Computational results on benchmark datasets are provided to support this analysis, and guide the selection of the most promising methods to generate these sequences.
Pedro Rocha, Rui Rodrigues, A. Miguel Gomes, Cláudio Alves

Measures in Sectorization Problems

Sectorization means dividing a whole into parts (sectors), a procedure that occurs in many contexts and applications, usually to achieve some goal or to facilitate an activity. The objective may be a better organization or simplification of a large problem into smaller sub-problems. Examples of applications are political districting and sales territory division. When designing/comparing sectors some characteristics such as contiguity, equilibrium and compactness are usually considered. This paper presents and describes new generic measures and proposes a new measure, desirability, connected with the idea of preference.
Ana Maria Rodrigues, José Soeiro Ferreira

Integrated Cutting and Production Planning: A Case Study in a Home Textile Manufacturing Company

In this paper we consider the problem of minimizing the waste of textile material in a Portuguese home textile manufacturing company. The company has a vertical structure covering the different production stages of the home textile, from weaving until the finished products. Production planning comprises different decisions: the definition of the widths and lengths of the fabric rolls to be produced, the number of fabric rolls to be used from stock or purchased and the definition of the cutting patterns to be applied to each width of the fabric roll, so that the waste is minimized. We propose a MIP model, solved by a column generation method, to tackle the problem.
Elsa Silva, Cátia Viães, José F. Oliveira, Maria Antónia Carravilla

The Cutting Stock Problem: A Case Study in a Manufacturer of Pet Vivaria

This paper addresses the problem of determining the cutting patterns of metal sheets, which arises in a manufacturer of metal cages, in order to minimize the waste, the number of cuts performed, the number of metal sheets used or a weighted combination of the three. A two stage approach, to solve a 2D guillotine cutting stock problem with single and multiple stock sizes, is presented and compared with the company approach and state-of-the-art algorithms. The results show great improvement compared to the company approach and a very good performance compared to state-of-the-art algorithms.
Carla Sousa, Elsa Silva, Manuel Lopes, António Ramos

Mathematics/Operations Research and Temperature on Cancer: A First Overview

In this study, the main characteristics of research works on Mathematical / Operations Research techniques applied to cancer and involving the temperature are described and analyzed. The information contained in those works was cataloged in accordance with specific key elements previously chosen. The developments on the theme are evaluated, observing what was done, describing the related applications, procedures and their practical implementation.
Ana Paula Teixeira, Regina de Almeida

Performance Assessment of Children and Youth Households

This study purposes a Data Envelopment Analysis (DEA) framework to assess the performance of Non-Profit Organizations that look after children and young people. The DEA method is used to assess the managerial efficiency of eight institutions from Bragança district, since 2010 to 2013. The model evaluates each institution concerning the reduction of operational and staff costs incurred in providing social services to the number of users observed in each unit. A fair policy for the allocation of subsidies is designed according to the performance of institutions in order to support the regulator.
Clara Bento Vaz, Jorge Alves, Ivo Mendes

Distribution Supply Chain Inventory Planning under Uncertainty

This paper considers a multi-echelon inventory/distribution system formed by N-warehouses and M-retailers that manages a set of diverse products in a dynamic environment. Transshipment at both regional warehouses and retailers levels is allowed. A mixed integer linear programming model is developed, where product demand at the retailers is assumed to be not known. The problem consists of determining the optimal reorder policy by defining a new concept of robust retailer order in a two level programming approach, which minimizes the overall system cost, including ordering, holding in stock and in transit, transportation, transshipping and lost sales costs. A case study based on a real retailer distribution chain is solved.
Joaquim Jorge Vicente, Susana Relvas, Ana Paula Barbosa-Póvoa


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