A dual mutation operator to solve the multi-objective production planning of perishable goods

• Tipo: Capítulo ou Parte de Livro
• Data: 2013

Autores

Bernardo Almada Lobo (Autor) FEUP; Pedro Amorim (Autor) FEUP; Carlos Henggeler Antunes (Autor) Outra

Livro

Título: Advances in Metaheuristics

2º Edição

Páginas: 77-97

ISBN: ISBN 978-1-4614-6321

Editora: Springer

Classificação Científica

FOS: Ciências da engenharia e tecnologias

CORDIS: Ciências Tecnológicas

Outras Informações

ID Authenticus: P-011-XE2

DOI: 10.1007/978-1-4614-6322-1_5

Abstract (EN): This work proposes a dual mutation operator that uses dual information to solve the multi-objective lot-sizing and scheduling problem arising in perishable goods production planning. This operator takes advantage of the hybrid structure of a multi-objective evolutionary algorithm, which combines the well-known NonDominated Sorting Genetic Algorithm and a mixed integer linear programming solver. Chromosomes are coded as strings of integer values ¿xing the production sequence. For each feasible individual, the reduced costs of the relaxed binary variables coming from the coding scheme are used to guide the mutation process. To assess the performance of this operator, a set of randomly generated instances based on a methodology reported in the literature is tested and evaluated with multi-objective performance metrics. The results indicate that the operator is able to achieve consistently better solutions in terms of an approximation to the Pareto solutions compared to the same solution procedure without the dual mutation.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 20