Two metaheuristics approaches for solving the traveling salesman problem: an Algerian waste collection case

Abstract

Waste collection remains a very important research area in waste management to deal with environmental degradation and health risks caused by daily waste quantities of the population. However, due to financial resources limitations, there is an increasing trend towards developing waste collection systems able to meet the different requirements related to the performance of the global collection cost, the tour scheduling and the capacity of each truck, the collection times, the fuel consumption and the overall traveled distance. In this work, we investigate the waste collection problem in Tlemcen City in Algeria. The problem is represented as a traveling salesman problem. Owing to the complexity of this real-life problem, two classes of metaheuristics known as powerful approaches are used to provide useful solutions for the addressed case. A Tabu Search algorithm and a simulated annealing (SA) algorithm are integrated in a decision-making graphical interface developed to help decision makers to plan their tours. The proposed algorithms are validated using data retrieved from all areas in Tlemcen. The results show that the SA performs the best to minimize the traveled distance in the vast majority of cases.