Isabel Gomes

In this work a two-stage scenario-based modeling approach is proposed in order to simultaneously deal with the design and planning decisions in supply chain networks, where both forward and reverse flows are considered (closed-loop supply chains) subject to uncertain conditions. A mixed integer linear programming (MILP) approach is developed with the underlying objective of profit maximization. Planning takes into account raw material acquisition and processing, storage and distribution of several products flowing through the network. Uncertainty is associated to the quantity and quality of the flow of products of the reverse network, which are directly affected by customers and sorting centers, respectively. The approach considers, by means of scenarios, the simultaneous integration of two important uncertainty sources, thus presenting an important modeling advantage, i.e. that of providing a better understanding of the CLSCs. The applicability of the formulation is tested with a real sized example of a Portuguese glass company.

The Portuguese directive 230/2004 established December 2006 as the dead-line for the legal targets of EEE recovery to be achieved. The EEE producers working in Portugal set up an organization whose mission is to design and manage this recovery network. A MILP model was previously developed to optimize the network design where, by considering EEE sources and recycling facilities locations as known, sorting centre locations were determined together with the planning of collection and sorting activities. In the present paper, the network planned by the Portuguese EEE organization is compared with the results provided by this early model. In addition, and taking into account new organizational objectives, where collecting and sorting entities should independently perform the associated activities, the developed model is further extended, in order to account for a new network level related to the collection and sorting activities, and the previous network is retrofitted.

Packaging waste collection systems are responsible to collect, within a geographic area, three types of packaging materials (paper, glass and plastic/metal) that are disposed by the final consumer into special bins. Those systems are often characterized by having a network with multiple depots that act as transfer and sorting stations, and where the vehicle fleet is based. However, each depot is often managed independently and not as a part of a unique system. In this work, four current tactical/operational practices that contribute to the independent management of each depot are analysed. The change of such practices is investigated and their impact assessed on the total collection cost. A solution methodology based on mathematical formulations is developed to plan service areas, vehicle routes and vehicle schedules taking into account new alternative solutions in managing the system as a whole. Such methodology is applied to a real case study of a company responsible for the collection of the packaging waste in 7 municipalities in mainland Portugal. New service areas, collection routes and vehicle schedules are defined and significant savings are obtained in terms of the total distance travelled as well as in terms of the number of required vehicles, resulting in a decreasing of the total system cost.

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This paper proposes a systematic methodology for supply chain planning optimization and assessment of different scenarios. This methodology will help companies throughout the difficult process of strategic decision-making in what concerns the design of an efficient supply chain structure. The proposed methodology allows the analysis of complex systems as it integrates a decision support tool developed to agile the process of scenario comparison, when designing network structures. This tool allows practitioners to take advantage of the optimization models without the need of learning modelling languages. An example based on a real case study is presented, showing the methodology/tool applicability.

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A general model for the design and planning of closed-loop supply chains is proposed. The model is both strategic and tactical in nature, containing two levels of decisions: the location of facilities and the planning of production, storage and distribution. Its mathematical formulation is solved using a standard Branch and Bound technique. The model applicability and accuracy are studied on a modified version of an already published case study.

A multi-product model for the design of global supply chains with reverse flows is proposed. Two levels of decisions are considered, one strategic and one tactical. The first is modelled through a macro perspective of time where the determination of the network structure and flows is accomplished. At tactical level, a micro perspective of time is considered, where production planning and inventory management are addressed in detail. A mixed integer linear programming formulation is developed which is solved with standard Branch and Bound techniques. The model accuracy and suitability are studied using a case study.

An European directive established that all EU countries must have, until the end of 2006, a recovery network for the electric and electronic equipment waste (WEEE). In Portugal, a group of producers formed a non-profit organization to design and manage this waste now. In this work, a model developed previously by the authors to design and plan a generic WEEE network is presented and applied to the Portuguese case. The results obtained are discussed and compared with the network that is currently operating.

In the last few decades there has been a massive growth in the Waste of Electric and ElectronicEquipment (WEEE). Part of these residues was already properly treated in some countries, but the lack of environmentally friendly options forced the European Union (EU) to take action. Two EU directives were created based on reduction, reutilization and recycling of WEEE. The need to properly designrecoverynetworks for such products appears as mandatory, where not only the economic aspects should be accounted for but also the environmental ones. The present paper addresses this problem and presents a generic optimization model for the design and planning of a recovery and treatment network of WEEE, minimizing both the costs and the environmental impacts that arise from the activity performed.

The model is applied to the real case of Amb3E, the Portuguese Association for the Management of Waste of Electric and ElectronicEquipment. Since its formation, in 2006, this organization has been registering an immense growth in the volume of residue collected, and faces now the necessity of reformulating its recoverynetwork. Both the actual cost structure and the best possible cost structure for Amb3E, given by the optimization of the model, are analyzed. These two scenarios are compared in order to turn clear the differences between them and to assess how the recoverynetwork of Amb3E can be improved through optimization. A similar analysis is performed from an environmental impacts perspective.

All European countries are building structures to support collection and recovery of electric and electronic waste (WEEE). In this work, the study of a Portuguese recovery network is presented. A MILP model is developed in order to determine the best WEEE network structure as well as the associated optimal plan. Several different analyses are performed.

Much attention is currently given to the study of supply chains. Most studies are, however, only concerned with forward chains, rendering reverse chains a field insufficiently covered. Few optimization models addressing either the design of reverse networks or the simultaneous design of forward and reverse networks have been presented. We propose a MILP model for the design and planning of an integrated forward and reverse chain. While minimizing cost, the network structure is defined simultaneously with production and storage planning. Dynamic aspects are accounted for using a two-time scale, fully interconnected structure, where at a macro time the network design is performed and at a micro time the planning is optimised. The deterministic model is extended and a scenario approach is applied to account for uncertainties in demand and return of products. A case study is solved and a common structure to all scenarios is obtained, while scenario dependent policies are defined for distribution, production and storage. The model generality is corroborated with good performance results.

The rapid growth of electric and electronic equipment waste (WEEE) transformed this waste stream into a worldwide problem. The Directive 2002/96/EC on electrical and electronic waste aims at the reduction of the environmental impact of WEEE, encouraging end-of-life management, eco design, life cycle analyses and extended producer responsibility. However, this legislation may not produce the results the legislator aimed for. In this work we analyse the environmental impact of a WEEE recovery network in the Portuguese context. With this aim, a model, previously developed by the authors for the optimal design of this network using economic indicators (Salema, 2007), was now adapted to design the network subjected to the minimization of environmental performance indices. The original mathematical formulation was found to be flexible and easily adapted to the two types of indices and the major differences between the optimal network configurations obtained, were identified and discussed.

This paper addresses the planning of recyclable waste collection systems while accounting for economic and environmental concerns. Service areas and vehicle routes are defined for multiple-depot logistics networks where different products have to be collected. The problem is modeled as a multi-product, multi-depot vehicle routing problem with two objective functions: distance and CO2 emissions minimization. A decomposition solution method is developed and applied to a real case-study. Six scenarios are studied regarding different service areas configuration and different objective functions. Savings up to 22% in distance and 27% in CO2 emissions are achieved, excelling economical and environmental goals.

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A Mixed Integer Linear Programming model for the design and planning of green supply chains is developed. Strategic and tactical decisions are taken, namely on facility location and capacity installation, supplier selection, technology selection, transportation network definition, supply planning, and product recovery. The aim of this work is to study the use of environmental indicators in these decisions while accounting for profit objectives. Different objective functions concerning environmental aspects are implemented. ReCiPe quantifies the environmental performance of the supply chain and combinations of ReCiPe’s midpoint categories allow a deeper analysis of the impact of these categories in strategic and tactical decisions. The goal is to understand if focusing on selected categories affects supply chain decisions and overall supply chain environmental impact. Net Present Value quantifies the economic performance and is used for lexicographic optimization. The model is applied to a case-study and important managerial insights are obtained. From a holistic point of view, it answers the question: how should supply chain environmental impact be assessed? From a case-study perspective, insights are obtained regarding what type of improvements should be implemented to reduce the environmental impact and how this would affect supply chain strategic and tactical decisions, along with economic performance.