Hybrid metaheuristics to solve a multi-product two-stage capacitated facility location problem

Chaves, Antonio Augusto [UNIFESP]; Mauri, Geraldo Regis; Biajoli, Fabricio Lacerda [UNIFESP]; Rabello, Rômulo Louzada; Ribeiro, Glaydston Mattos; Lorena, Luiz Antônio Nogueira [UNIFESP]

Hybrid metaheuristics to solve a multi-product two-stage capacitated facility location problem

Arquivos

TSCFLP_MP_ITOR.pdf(633.38 KB)

Data

2021

Autores

Chaves, Antonio Augusto [UNIFESP]

Mauri, Geraldo Regis

Biajoli, Fabricio Lacerda [UNIFESP]

Rabello, Rômulo Louzada

Ribeiro, Glaydston Mattos

Lorena, Luiz Antônio Nogueira [UNIFESP]

Tipo

Artigo

Resumo

This paper presents two hybrid metaheuristics to solve a multi-product two-stage capacitated facility location prob- lem (MP-TSCFLP). In this problem, a set of different products must be transported from a set of plants to a set of intermediate depots (first stage) and from these depots to a set of customers (second stage). The objective is to minimize the cost related to open plants and depots plus the cost for transporting the products from the plants until the customers satisfying demand and capacity constraints. Recently, the methods Clustering Search (CS) and Biased Random-Key Genetic Algorithm (BRKGA) were successfully applied to solve a single-product problem (SP-TSCFLP). Therefore, in this paper we propose adaptations and implementations of these methods for handling with a multi-product approach. To the best of our knowledge, CS and BRKGA presented the best results for the SP-TSCFLP and both have not yet been applied to solve the problem with multiple products. Four sets of large- sized instances with different characteristics are proposed and computational experiments compare the obtained results to those from a commercial solver.