Reducing pollutant emissions in a waste collection vehicle routing problem using a variable neighborhood tabu search algorithm: a case study

Abstract

This paper focuses on designing waste collection routes with a single landfill using eco-efficiency as a performance indicator. In this problem, there are a limited number of heterogeneous vehicles based at a single depot. Empty vehicles leave the depot, collect waste from a set of locations and drop off the collected waste at a specific landfill. Then, vehicles leave the landfill and may collect more waste from other locations or return empty to the depot. Traditional performance indicators in vehicle routing problems are mainly focused on economic objectives, not explicitly considering environmental issues. In this paper, a mathematical model is presented with an eco-efficient objective function that takes into account external costs (climate change and air pollution). The COPERT model is used for estimating fuel consumption, carbon dioxide and pollutant emissions. The problem is first heuristically solved using a semi-parallel construction algorithm. Then, solutions are improved by a variable neighborhood tabu search algorithm developed for this problem. The algorithm is validated for a real problem in the municipality of Alcalá de Guadaíra, within the metropolitan area of Seville (Spain). Results obtained on a set of case studies improve the solution that is currently implemented in the municipality, in terms of total distance traveled, carbon dioxide emissions and pollutant emissions.

Advertising through UAVs: Optimized path system for delivering smart real‐estate advertisement materials

“…Other recent studies have also utilized these algorithms and highlighted their higher performance. [35][36][37][38] These beneficial studies have indicated that greedy, interroute, intraroute, and Tabu are interlinked and high-performance algorithms for solving vehicle routing issues. Accordingly, the current study adopts and subsequently explains these algorithms.…”

“…Lastly, a Tabu search is purposed to make improvements to the promising solutions obtained from the upper layers. Other recent studies have also utilized these algorithms and highlighted their higher performance 35–38 . These beneficial studies have indicated that greedy, interroute, intraroute, and Tabu are interlinked and high‐performance algorithms for solving vehicle routing issues.…”

Transportation Risk Control of Waste Disposal in the Healthcare System with Two-Echelon Waste Collection Network

“…Some works are devoted to carbon emission reduction and other environmental protection aspects [13,14]. In the field of waste collection, Molina et al [15] use eco-efficiency as a performance indicator which takes carbon dioxide emissions and pollutant emissions into account for the waste collection route decision. Farrokhi-Asl et al [16] present a multiobjective mathematical model considering a sustainable collection network for the collection, treatment, recycling, and disposal of hazardous waste.…”

Heterogeneous Fleet Green Vehicle Routing Problem: A Literature Review

“…Moreover, for metaheuristic method, previous research used split-based adaptive tabu search (SATS) [64], time varying (TVa) and particle swarm optimization with greedy mutation operator (PSOGMO) [89], non-dominated sorting genetic algorithm II (NSGA II) [32,93], Ant colony optimization (ACO) [90], variable neighborhood search [94], variable neighborhood tabu search algorithm [91], and GA [92]. Besides, in multiobjective GVRP there are some hybrid methods that have been implemented such as exact-exact, exactmetaheuristic, and heuristic-metaheuristic.…”