Application of Fuzzy Robust Approach for Location-Routing of Urban Waste Collection Facilities using Genetic Algorithm

Document Type : Scientific - Research

Authors
1 Associate Professor, Faculty of Business and Economics, Persian Gulf University, Bushehr, Iran
2 Assistant Professor, Faculty of Business and Economics, Persian Gulf University, Bushehr, Iran
Abstract
Today, the problem of locating waste tanks and routing waste collection vehicles is closely related to the health of society and the environment. In this article, the positioning-routing problem of the periodic arc along with the intermediate discharge stations is studied under conditions of uncertainty, the purpose of which is to reduce the number of active places for waste collection in Bushehr city, to determine the optimal routes. In order to serve all the areas with the demand of the urban graph network during the week and the number of vehicles is required. A mixed integer linear programming model is developed along with taking into account the fuzzy demand to optimize the problem, and multi-objective genetic algorithm is used for the approximate solution of the problem. To evaluate the efficiency of the proposed algorithm, CPLEX solver of GAMS software is used to solve problems with small and medium dimensions. In the current research, since it is very difficult to accurately and correctly identify the distribution of parameters in the problem of waste management planning, and most of the required data have uncertainty, robust optimization approach and intuitive fuzzy approach were used to model the research problem. Is. The results of this research show that the value of the objective functions determined in the fuzzy robust method is less than the deterministic method. Among the other results of this research, we can mention a 9% reduction in the amount of use of required tanks allocated to waste collection sites, as well as a 52% reduction in active sites for waste collection.

Keywords


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Volume 15, Issue 3 - Serial Number 60
Winter 2024
Pages 3821-3843

  • Receive Date 21 October 2022
  • Revise Date 26 November 2022
  • Accept Date 28 November 2022