Routing in waste collection: A simulated annealing algorithm for an Argentinean case study

Abstract

<abstract> <p>The management of the collection of Municipal Solid Waste is a complex task for local governments since it consumes a large portion of their budgets. Thus, the use of computer-aided tools to support decision-making can contribute to improve the efficiency of the system and reduce the associated costs, especially in developing countries, which usually suffer from a shortage of resources. In the present work, a simulated annealing algorithm is proposed to address the problem of designing the routes of waste collection vehicles. The proposed algorithm is compared to a commercial solver based on a mixed-integer programming formulation and two other metaheuristic algorithms, i.e., a state-of-the-art large neighborhood search and a genetic algorithm. The evaluation is carried out on both a well-known benchmark from the literature and real instances of the Argentinean city of BahȪa Blanca. The proposed algorithm was able to solve all the instances, having a performance similar to the large neighborhood procedure, while the genetic algorithm showed the worst results. The simulated annealing algorithm was also able to improve the solutions of the solver in many instances of the real dataset.</p> </abstract>

Retracted: Study on Optimization of Interior Ballistic Performance of Cased Telescoped Ammunition Based on Improved Firefly Algorithm

“…In recent years, the modern intelligent optimization algorithm has been employed to different fields, among which genetic algorithm (GA) [6][7][8][9], simulated annealing algorithm (SAA) [10][11][12] and particle swarm optimization algorithm (PSO) [13][14][15][16] have been extensively used. Some optimization algorithms, such as genetic algorithm [17][18][19][20] and particle swarm optimization algorithm [21], have been successfully applied to the research of interior ballistic performance optimization of artillery, which, however, have their own shortcomings that are difficult to overcome.…”

Optimization of waste collection through the sequencing of micro-routes and transfer station convenience analysis: An Argentinian case study

“…If the solver is able to find the optimal solution, this value would be 0%. However, in computationally complex problems, such as the routing problems that are addressed in this paper (Toth and Vigo, 2002), it is difficult to converge to an optimal result in practical computing times (Rossit et al, 2021). Significant differences in the execution of each model are observed in the values.…”

“…Moreover, some works explicitly consider the location of garbage accumulation points taking into account a proxy to posterior routing costs among the different objectives (Rossit et al, 2018(Rossit et al, , 2020. Other works addressed the waste collection problem considering the previous location of waste bins (Fermani et al, 2020;Rossit et al, 2021), while others considered both problems simultaneously, that is, optimizing the sizing of waste bins and designing the collection routes (Mahéo et al, 2020(Mahéo et al, , 2023. Finally, in Vazquez et al (2020), an analysis of the composition and amount of waste in Bahía Blanca was performed based on a thorough field work.…”

Waste Collection Vehicle Routing Problem with TimeWindows for Route Optimization of Garbage Transport Vehicles

“…The problem of waste collection is a problem faced by an area, especially urban areas Lu et al, 2015. In this paper, we study a variant of the Vehicle Routing Problem (VRP) as a waste collection vehicle routing problem with time windows. Rossit et al (2021) proposed a simulated annealing algorithm to overcome the route of garbage collection vehicles based on mixed integer programming and metaheuristic methods, large neighborhood search, and genetic algorithms. The waste collection vehicle route problem is modeled with a scheduling strategy and an environmentally friendly solution is sought (Korcyl et al, 2019;Lu et al, 2015).…”