Advanced planning for minimizing makespan with load balancing in multi-plant chain
- Authors
- Moon, C; Seo, Y
- Issue Date
- 15-10월-2005
- Publisher
- TAYLOR & FRANCIS LTD
- Keywords
- advanced planning; supply-chain management; multi-plant chain; multi-objective mixed integer programming model; adaptive genetic algorithm
- Citation
- INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, v.43, no.20, pp.4381 - 4396
- Indexed
- SCIE
SCOPUS
- Journal Title
- INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- Volume
- 43
- Number
- 20
- Start Page
- 4381
- End Page
- 4396
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/123212
- DOI
- 10.1080/00207540500142449
- ISSN
- 0020-7543
- Abstract
- This paper deals with the advanced planning problem for minimizing makespan with workload balancing considering capacity constraints, precedence relations, and alternative resources with different operation times in a multi-plant chain. The problem is formulated as a multi-objective mixed integer programming (mo-MIP) model which determines the operations sequences with resource selection and schedules. In this model, a single unique solution does not exist since the objectives may be conflicting, which have to be globally minimized with respect to the two objectives. For effectively solving the alternative solutions of the advanced planning model, we develop an adaptive genetic algorithm (aGA) approach with the adaptive recombination functions and the revised adaptive weighted method. The experimental results are presented for the advanced planning problems of various sizes to describe the performance of the proposed aGA approach. The performance of the aGA approach is also compared with that of the Moon, Li and Gen (MLG) method.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - College of Engineering > School of Industrial and Management Engineering > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.