A hybrid multi-population genetic algorithm applied to solve the multi-level capacitated lot sizing problem with backlogging

Author(s)

Motta Toledo, Claudio Fabiano ^[1] ; Ribeiro de Oliveira, Renato Resende ^[2] ; Franca, Paulo Morelato ^[3]

Affiliation

^[1] Univ Sao Paulo, Inst Math & Comp Sci, BR-05508 Sao Paulo - Brazil

^[2] Univ Fed Lavras, Dept Comp Sci, Lavras, MG - Brazil

^[3] Univ Estadual Paulista, Dept Math & Comp, Sao Paulo - Brazil

• Document type: Journal article
• Source: Computers & Operations Research; v. 40, n. 4, p. 910-919, APR 2013.
• Web of Science Citations: 30

Abstract

The present paper proposes a new hybrid multi-population genetic algorithm (HMPGA) as an approach to solve the multi-level capacitated lot sizing problem with backlogging. This method combines a multi-population based metaheuristic using fix-and-optimize heuristic and mathematical programming techniques. A total of four test sets from the MULTILSB (Multi-Item Lot-Sizing with Backlogging) library are solved and the results are compared with those reached by two other methods recently published. The results have shown that HMPGA had a better performance for most of the test sets solved, specially when longer computing time is given. (C) 2012 Elsevier Ltd. All rights reserved. (AU)

• FAPESP's process: 10/10133-0 - Cutting, packing, lot-sizing and scheduling problems and their integration in industrial and logistics settings
• Grantee: Reinaldo Morabito Neto
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 11/15581-3 - Environment for development of methods applied to optimization problems
• Grantee: Márcio da Silva Arantes
• Support Opportunities: Scholarships in Brazil - Master
• FAPESP's process: 11/15534-5 - Hybrid heuristics and metaheuristics applied to the multi-level capacitated lot sizing problem
• Grantee: Claudio Fabiano Motta Toledo
• Support Opportunities: Regular Research Grants