Isabel Gomes

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 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.

The European Union directive for electric and electronic waste, published in 2003, enforced all European countries to meet some targets concerning the recycling and recovery of these products. This directive was transposed to the Portuguese legislation in 2004. Following this, a group of EEE producers set up an organization (Amb3e) whose mission was to design and manage a nationwide recovery network for WEEE, which will be the subject matter of this work. A generic MILP model is proposed to represent this network, which is applied to its design and planning, where the best locations for collection and sorting centres are chosen simultaneously with the definition of a tactical network planning. Several analyses are performed to provide further insights regarding the selection of these alternative locations. The results gave support to the company strategic expansion plans for a high number of centres to be opened and to their location near the major WEEE sources.

In this work, the design and operation planning of a multi-period, multi-product closed-loop supply chain is addressed. Recovered end-of-life products from customers are evaluated in disassembly centers and accordingly are sent back to factories for remanufacturing, or leave the network either by being sold to third parties or by being sent to disposal. Typical uncertain parameters are product demand, production cost, and returned product volume and evaluation, among others. So, stochastic optimization approaches should be used for problem solving, where different topology decisions on the timing, location and capacity of some entities (factories, and distribution and sorting centers) are to be considered along a time horizon. A two-stage multi-period stochastic mixed 0–1 bilinear optimization model is introduced, where the combined definition of the available entities at the periods and the products’ flow among the entities, maximizes the net present value of the expected total profit along the time horizon. A version of the mixture of chance-constrained and second order stochastic dominance risk averse measures is considered for risk management at intermediate periods of the time horizon. Given the high dimensions of the model it is unrealistic to look for the optimality of the solution in an affordable computing effort for current hardware and optimization software resources. So, a decomposition approach is considered, namely a Fix-and-Relax decomposition algorithm. For assessing the computational validation of the modeling and algorithmic proposals, pilot cases are taken from a real-life glass supply chain network whose main features are retained.

In this work the design of a reverse distribution network is studied. Most of the proposed models on the subject are case based and, for that reason, they lack generality. In this paper we try to overcome this limitation and a generalized model is proposed. It contemplates the design of a generic reverse logistics network where capacity limits, multi-product management and uncertainty on product demands and returns are considered. A mixed integer formulation is developed which is solved using standard B&B techniques. The model is applied to an illustrative case.

The present work aims to support tactical and operational planning decisions of reverse logistics systems while considering economical, environmental and social objectives. In the literature, when addressing such systems economical aspects have been often used, while environmental concerns have been only recently emerging. The social component is the one less studied, and rarely the combination of the three concerns has been analyzed. This work address the three objectives and was motivated by the challenge of supporting decisions makers when managing a real case study of a recyclable waste collection system, where strategic decisions on the number and location of depots, vehicles and containers were taken beforehand. Tactical and operational decisions are studied involving the establishment of service areas for each depot and the definition and scheduling of collection routes for each vehicle. Such decisions should represent a compromise solution between the three objectives considered and support a sustainable reverse logistics plan. A multi-objective solution approach based on mixed-integer linear programming models is developed. Trade-offs between the objectives are discussed. Moreover the solutions obtained when each objective is tackled individually are compared between themselves and with the balanced solution.

This research has been motivated by a real-life problem of a waste cooking oil collection system characterized by the existence of multiple depots with an outsourced vehicle fleet, where the collection routes have to be plan. The routing problem addressed allows open routes between depots, i.e., all routes start at one depot but can end at the same or at a different one, depending on what minimizes the objective function considered. Such problem is referred as a Multi-Depot Vehicle Routing Problem with Mixed Closed and Open Inter-Depot Routes and is, in this paper, modeled through a Mixed Integer Linear Programming (MILP) formulation where capacity and duration constraints are taken into account. The model developed is applied to the real case study providing, as final results, the vehicle routes planning where a decrease of 13% on mileage and 11% on fleet hiring cost are achieved, when comparing with the current company solution.

The increase in societal awareness towards environmental issues has accrued the responsibility of goods producers, which at present came to encompass the entire product life cycle. Recently, the efficient design and operation of supply chains with return flows have, in particular, become a major challenge for many companies, given the high number of factors involved and their intricate interactions. In this paper, a multi-period and multi-product network model for the simultaneous design and planning of supply chains with reverse flows is proposed. A graph approach based on the conventional concepts of nodes and arcs is employed to model the network, where it is assumed that any network node is a transformation point of inbound into outbound flows, which in the limit may not differ, and that related arcs describe products flows along the chain. In here the formulation of time adopts a management perspective, i.e., the strategic design of the supply chain is dealt simultaneously with the tactical planning of its operation, which covers supply, production, storage and distribution. An example based on a Portuguese industry case is studied in order to validate both the applicability and adequacy of the model to real world problems.

In this paper, a strategic location-allocation model is developed for the simultaneous design of forward and reverse supply chains. Strategic decisions such as network design are accounted for together with tactical decisions, namely, production, storage and distribution planning. The integration between strategic and tactical decisions is achieved by considering two interconnected time scales: a macro and a micro time. At macro level, the supply chain is designed in order to account for the existing demands and returns, whose satisfaction is planned simultaneously at the micro level where tactical decisions are taken. A Mixed Integer Linear Programming formulation is obtained which is solved to optimality using standard Branch & Bound techniques. Finally, the model accuracy and applicability is illustrated through the resolution of a case study.

Abstract This work presents ToBLoOM – Triple Bottom Line Optimization Modelling, a decision support tool for the design and planning of sustainable supply chains. It consists of a multi-objective mixed integer linear programming model which integrates several interconnected decisions: facility location and capacity determination; supplier selection and purchase levels definition; technology selection and allocation; transportation network definition including both unimodal and intermodal options; supply planning; product recovery and remanufacturing. The three pillars of sustainability are addressed as objective functions: economic, through Net Present Value; environmental through the Life Cycle Analysis methodology ReCiPe; and social through a developed GDP-based metric. Uncertainty is considered using a stochastic ToBloOM. This applied to a case of a European based company with markets in Europe and South America. This work contributes to the literature by building on several identified research gaps such as the need for an integrated approach that allows simultaneous assessment of different interacting supply chain decisions, the need to explicitly assess the environmental impact in closed-loop supply chains, the need to assess the impact of supply chains on society, and the need for a multi-objective tool that includes all the three pillars of sustainability. Strategies towards a more sustainable supply chain are also derived from this work.

In this paper, an MILP formulation is proposed for the design of a reverse logistics network based on a warehouse location–allocation model, which optimizes, simultaneously, the forward and reverse networks. A single product model with unlimited capacity is first defined. Subsequently, the model is extended to a multi-product capacitated recovery network model, where capacity limitations and a multi-product system can be considered. The proposed model is compared to published work in the field, where different model assumptions have been proposed. Two cases are described so as to gain a better insight into the model and allow a comparative analysis.