Uma abordagem híbrida para a solução do problema de roteamento de veículos com múltiplos depósitos e frota heterogênea: algoritmo genético e busca tabu

Abstract

This paper presents a Hybrid Algorithm (AH) applied to the Problem of Vehicle Routing with Multiple-Deposit and Heterogeneous Fleet (MDFHPRV). A number of customers are served with a fixed number of vehicles of different sizes by multi-depot, subject to capacity constraints of the vehicle. The meta-heuristics used in AH construction are Genetic Algorithm (GA) and Tabu Search (BT). The AG uses Partial Mapped Crossover (PMX), Two Part Chromosome Crossover (TCX) and Order Crossover (OX) operators, the Exchange mutation operator, and the Local Search Algorithm (ABL). BT uses the Exchange, Retrieve, and Insertion and Displacement methods. Diversification policies was analyzed in the ABL and the intensification with the neighborhood generation strategies in BT. Standard sets of test problems are used to execute the proposed algorithms. The obtained results, compared to other authors, presented good solutions for different sizes of test problems.