An application of the augmented ε-constraint method to design a municipal sorted waste collection system

Abstract

The separation at the source of Municipal Solid Waste (MSW) is an initiative that facilitates the subsequent recycling work and contributes to palliate the negative impacts of the traditional unsorted collection system. This paper presents a multi-objective integer linear programming model of the determination of the optimal location of assorted waste bins in an urban area. We consider, jointly, the objectives of minimizing the investment cost and the average distance from the dwellings to the bins. The model was applied in simulated instances of an Argentinian medium-size city, contributing to the transition from the current door-to-door based system to a community bins system. To solve this problem, we apply both the weighting method, which has been used to solve similar problems in the literature, and a novel version of the augmented ε-constraint method (AUGMECON2). The results over simulated scenarios show that, in general, AUGMECON2 has a better performance, yielding a larger number of efficient solutions at lower computation times.Growing Science Ltd. All rights reserved. 7

Application of a methodology to design a municipal waste pre-collection network in real scenarios

“…The majority of them have focused on the proposal of optimization tools for locating waste bins. We found different authors that have applied exact approaches (Rossit et al, 2017; Coutinho-Rodrigues et al, 2012 ), and heuristic approaches (Boskovic and Jovicic, 2015; Ghianni et al, 2012; Toutouh et al, 2019). However, few of these authors have proposed comprehensive methodologies for locating disposal points that involve the different stages of designing this network.…”

“…Most of the waste is taken to the landfill, without any classification or processing, which is a common practice in developing countries (Boskovic et al, 2016). The landfill, due to its intensive use and the semiarid climate of the area that hinders waste biodegradation, is almost at the limit of its capacity (Rossit et al, 2017). In addition, the operation of the landfill of Bahía Blanca represents the most expensive contract managed by the municipality.…”

“…To solve the optimization problem, we used a mathematical model of mixed-integer programming based on the capacitated facility location problem (CFLP). For this case study, the proposed formulation was based on the works of Rossit et al (2017) and Herrán Symonds (2019). This model consists in optimizing the location of waste disposal points, by minimizing the investment costs, given the maximum area available to install the bins and their capacities.…”

Solving a multi-objective manufacturing cell scheduling problem with the consideration of warehouses using a simulated annealing based procedure

“…In order to find the real Pareto Front of each instance and validate the proposed metaheuristic, we applied the augmented ε-constraint method presented in Mavrotas and Florios (2013). This approach is a novel variation of the original method developed by Haimes (1971), having several advantages not only over the traditional ε-constraint but also over another popular multi-objective approach as it is the weighted sum (Mavrotas, 2009;Mavrotas & Florios, 2013;Rossit et al 2017). Namely, it guarantees the Pareto optimality of the solution and reduces the computing time by avoiding repeated solutions.…”

A trade-off between productivity and cost for the integrated part quality inspection and preventive maintenance planning under uncertainty

“…For example, this method does not guarantee the efficiency of the achieved solutions (i.e. achieving weakly efficient solutions) (Rossit et al 2017). Mavrotas (2009) explained some of these drawbacks and proposed an improved version of the ε-constraint technique, called 'augmented ε-constraint method'.…”