Using meta-heuristic algorithms and hybrid of them to solve multi compartment Vehicle Routing Problem

The Traveling Salesman Problem (TSP) and the Vehicle Routing Problem (VRP) are two of the most popular problems in the field of combinatorial optimization. Due to the study of these two problems, there has been a significant growth in families of exact and heuristic algorithms being used today. The purpose of this paper is to show how their study has fostered developments of the most popular algorithms now applied to the solution of combinatorial optimization problems. These include exact algorithms, classical heuristics and metaheuristics.

This paper presents a methodology for solving the municipal waste collection problem in urban areas. The problem is treated as a distance-constrained capacitated vehicle routing problem for municipal waste collection (DCCVRP-MWC). To solve this problem, four meta-heuristic algorithms were used: Genetic algorithm (GA), Simulated annealing (SA), Particle swarm optimization (PSO) and Ant colony optimization (ACO). Vehicle guidance plays a huge role in large transportation companies, and with this test, we propose one of several algorithms for solving urban waste collection problems.

Companies of chartered transport of passengers need to manage routes with boarding points, based on the location of the passengers. As the number of routes grow, the task of manually manage and optimize routings becomes inviable. The vehicle routing problem characterizes inside this scenario, branching into specific problems, that need different solutions for each case. Meta-heuristics are usually used to build solver algorithms for these problems. Constraint programming was chosen for helping build the solver. The main objective of the work was, to develop a system performing the solution of routings in an automatized way, by utilization of constraint programming and meta-heuristic algorithms. To minimize transport costs, travel time, and maximize the use of vehicles in an efficient and planned manner. The tests were carried out in conjunction with a routing administrator, to validate the use of the application within the research field. From the evaluations made, they demonstrated the utility of the software within its purpose. Of which it was observed that the product of this research, helped in the construction of an automated fleet consulting tool, being able to dynamically point out the distribution and operationality of a fleet of chartered vehicles in the transportation of passengers.