A hybrid approach based on genetic algorithm and nearest neighbor heuristic for solving the capacitated vehicle routing problem

• Published in: Acta scientiarum. Technology Vol. 40; no. 1; pp. 36708 - e36708
• Main Authors: Lima, Stanley Jefferson de Araújo, Araújo, Sidnei Alves de, Schimit, Pedro Henrique Triguis
• Format: Journal Article
• Language: English
• Published: Maringa Editora da Universidade Estadual de Maringá - EDUEM 01.01.2018; Universidade Estadual de Maringá
• Subjects: capacitated vehicle routing problem; complex networks; downhill; Genetic algorithms; Gillett & Miller; Heuristic; nearest neighbor; Route planning; Routing; Shortest-path problems; Traveling salesman problem; Vehicle routing
• ISSN: 1806-2563; 1807-8664; 1807-8664; 1806-2563
• DOI: 10.4025/actascitechnol.v40i1.36708

This work presents a hybrid approach called GA-NN for solving the Capacitated Vehicle Routing Problem (CVRP) using Genetic Algorithms (GA) and Nearest Neighbor heuristic (NN). The first technique was applied to determine the groups of customers to be served by the vehicles while the second is responsible to build the route of each vehicle. In addition, the heuristics of Gillett & Miller (GM) and Downhill (DH) were used, respectively, to generate the initial population of GA and to refine the solutions provided by GA. In the results section, we firstly present experiments demonstrating the performance of the NN heuristic for solving the Shortest Path and Traveling Salesman problems. The results obtained in such experiments constitute the main motivation for proposing the GA-NN. The second experimental study shows that the proposed hybrid approach achieved good solutions for instances of CVRP widely known in the literature, with low computational cost. It also allowed us to evidence that the use of GM and DH helped the hybrid GA-NN to converge on promising points in the search space, with a small number of generations.