{"title":"Waste Collection Optimisation: A Path to a Green and Sustainable City of Makkah","authors":"H. Algethami, Ghada Talat Alhothali","doi":"10.3390/logistics7030054","DOIUrl":null,"url":null,"abstract":"Background: Saudi Arabia is a leading country endorsing a sustainable future, from policymaking and investment to infrastructure development. One of the rising concerns in Saudi Arabia's Vision 2030 is solid waste management, especially in Makkah. The Solid Waste Collection Problem (SWCP) refers to the route optimisation of waste collection trucks visiting containers across various locations. Manually generated routes might contain some mistakes, and constructing and revising designed solutions can take a long time. Thus, there is a need to find optimal and fast solutions to this problem. Solving this problem demands tackling numerous routing constraints while aiming to minimise the operational cost. Since solid waste has a significant impact on the environment, reducing fuel consumption must be an objective. Methods: Thus, a mixed-integer programming model is proposed in this paper while using the time-oriented nearest neighbour heuristic. The goal is to investigate their performance on nine existing instances of SWCP in the city of Makkah. The proposed model is implemented in the Gurobi solver. The time-oriented nearest neighbour heuristic constructs the initial solution and is then re-optimised using Google OR-tools. Results: Using the greedy method to construct a solution for this problem generated better solutions when compared to the results obtained without the greedy method. Computational times are also improved by 55.7% on the problem instances. Conclusions: The findings confirm the competitive performance of the proposed method in terms of computational times and solution quality.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.6000,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Logistics-Basel","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/logistics7030054","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 1
Abstract
Background: Saudi Arabia is a leading country endorsing a sustainable future, from policymaking and investment to infrastructure development. One of the rising concerns in Saudi Arabia's Vision 2030 is solid waste management, especially in Makkah. The Solid Waste Collection Problem (SWCP) refers to the route optimisation of waste collection trucks visiting containers across various locations. Manually generated routes might contain some mistakes, and constructing and revising designed solutions can take a long time. Thus, there is a need to find optimal and fast solutions to this problem. Solving this problem demands tackling numerous routing constraints while aiming to minimise the operational cost. Since solid waste has a significant impact on the environment, reducing fuel consumption must be an objective. Methods: Thus, a mixed-integer programming model is proposed in this paper while using the time-oriented nearest neighbour heuristic. The goal is to investigate their performance on nine existing instances of SWCP in the city of Makkah. The proposed model is implemented in the Gurobi solver. The time-oriented nearest neighbour heuristic constructs the initial solution and is then re-optimised using Google OR-tools. Results: Using the greedy method to construct a solution for this problem generated better solutions when compared to the results obtained without the greedy method. Computational times are also improved by 55.7% on the problem instances. Conclusions: The findings confirm the competitive performance of the proposed method in terms of computational times and solution quality.