An adaptive iterated local search heuristic for the Heterogeneous Fleet Vehicle Routing Problem

Autor(es)

Maximo, Vinicius R. ; Cordeau, Jean-Francois ; Nascimento, Maria C. V.

• Tipo de documento: Artigo Científico
• Fonte: Computers & Operations Research; v. 148, p. 12-pg., 2022-08-24.

Resumo

The Heterogeneous Fleet Vehicle Routing Problem (HFVRP) is an important variant of the classical Capacitated Vehicle Routing Problem (CVRP) that aims to find routes that minimize the total traveling cost of a heterogeneous fleet of vehicles. This problem is of great interest given its importance in many industrial and commercial applications. In this paper, we present an Adaptive Iterated Local Search (AILS) heuristic for the HFVRP. AILS is a local search-based meta-heuristic that achieved good results for the CVRP. The main characteristic of AILS is its adaptive behavior that allows the adjustment of the diversity control of the solutions explored during the search process. The proposed AILS for the HFVRP was tested on benchmark instances containing up to 360 customers. The results of computational experiments indicate that AILS outperformed state-of-the-art metaheuristics on 87% of the instances. (AU)

• Processo FAPESP: 13/07375-0 - CeMEAI - Centro de Ciências Matemáticas Aplicadas à Indústria
• Beneficiário: Francisco Louzada Neto
• Modalidade de apoio: Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs
• Processo FAPESP: 19/22067-6 - Estratégias de aprendizado para busca heurística em problemas de otimização combinatória
• Beneficiário: Mariá Cristina Vasconcelos Nascimento Rosset
• Modalidade de apoio: Bolsas no Exterior - Pesquisa
• Processo FAPESP: 16/01860-1 - Problemas de corte, empacotamento, dimensionamento de lotes, programação da produção, roteamento, localização e suas integrações em contextos industriais e logísticos
• Beneficiário: Reinaldo Morabito Neto
• Modalidade de apoio: Auxílio à Pesquisa - Temático