Multi-population genetic algorithm to solve the synchronized and integrated two-level lot sizing and scheduling problem

Autor(es)

Toledo, C. F. M. ^[1] ; Franca, P. M. ^[2] ; Morabito, R. ^[3] ; Kimms, A. ^[4]

Afiliação do(s) autor(es)

^[1] Univ Fed Lavras, Dept Ciencia Computacao, BR-37200000 Lavras, MG - Brazil

^[2] Univ Estadual Paulista, Dept Matemat Estat & Computacao, Fac Ciencias & Tecnol, BR-19060900 Presidente Prudente, SP - Brazil

^[3] Univ Fed Sao Carlos, Dept Engn Producao, BR-13565905 Sao Carlos, SP - Brazil

^[4] Univ Duisburg Essen, Dept Technol & Operat Management, D-47048 Duisburg - Germany

• Tipo de documento: Artigo Científico
• Fonte: INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH; v. 47, n. 11, p. 3097-3119, 2009.
• Citações Web of Science: 46

Resumo

This paper introduces an evolutionary algorithm as a procedure to solve the Synchronized and Integrated Two-Level Lot Sizing and Scheduling Problem (SITLSP). This problem can be found in some industrial settings, mainly soft drink companies, where the production process involves two interdependent levels with decisions concerning raw material storage and soft drink bottling. The challenge is to simultaneously determine the lot-sizing and scheduling of raw materials in tanks and soft drinks in bottling lines, where setup costs and times depend on the previous items stored and bottled. A multi-population genetic algorithm approach with a novel representation of solutions for individuals and a hierarchical ternary tree structure for populations is proposed. Computational tests include comparisons with an exact approach for small-to-moderate-sized instances and with real-world production plans provided by a manufacturer. (AU)

• Processo FAPESP: 00/02609-2 - Problema conjunto de dimensionamento de lote e programação da produção
• Beneficiário: Claudio Fabiano Motta Toledo
• Modalidade de apoio: Bolsas no Brasil - Doutorado