Study of the GELS-GA algorithm on CVRP and its applications

The Capacitated Vehicle Routing Problem (CVRP) is a variant of the VRP problem. The CVRP problem is an optimization problem that can be solved using metaheuristic optimization methods such as Gravitational Emulation Local Search with Genetic Algorithm (GELS-GA). The focus of this article is the implementation of the GELS-GA algorithm on CVRP with the Borland Delphi 7 application, tested with several datasets and compared to other algorithms. Program inputs are population size, crossover probability, mutation probability, maximum iteration, vehicle capacity, number of points, and demand for each customer. The program output is in the form of route results with mileage and route images. The results of the trial using 3 VRP datasets consisting of 45 points, 60 points, and 80 points were experimented 10 times with the results compared with the LNS-ACO algorithm. Based on the test results, the GELS-GA solution is better than the LNS-ACO algorithm in the A-n60-k09 code and A-n80-k10 code. In code A-n45-k06 the GELS-GA algorithm does not have a better solution than LNS-ACO. The GELS-GA algorithm on CVRP can be used to solve distribution optimization problems.