Optimization of Vehicles Routing Problem using GA For AL-Rasheed municipality, Baghdad, Iraq

Abstract

There are several problems with waste collection, transportation, processing, and disposal, particularly in major cities. The frequency of garbage collection is an important concern for municipal control. If waste is not disposed of properly, environmental problems such as air pollution and groundwater contamination may occur. This problem raises the alarm for the need for specialized solutions for averting potential calamities that might occur throughout the world. Before deploying to actual situations, computer modeling and planning of waste collection are frequently performed to minimize the negative impact solid waste can have on the environment. As a result, choosing the optimal waste collection policy has a large effect on cost savings. The current study's objective is to apply a genetic algorithm to reach the goals, illustrating the process of selecting the optimal route for the vehicle with the lowest time and greatest weight among several paths. The other goal is to create a schedule for the vehicles in order to decrease them. The schedule will minimize vehicle-related costs such as maintenance, gasoline, work staff salaries, and other vehicle-related costs. In the current study, the MATLAB application R2020a is used to apply reliable data of 10 vehicles from the AL-Rasheed Municipality waste collection vehicles after processing it to be acceptable with the GA. After optimizing the time for routes and weights of lifted trash, the majority of the results improved dramatically. The results reveal that the top five vehicles (8, 6, 7, 1, 4) have a great percentage improvement in the number of collection points (133.3%, 100%, 100%, 66.7%, and 50%), respectively.