Genetic algorithm-based integrated production planning considering manufacturing partners

Hosang Jung, Iksoo Song, Bongju Jeong

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

This paper deals with an integrated production planning problem in the presence of manufacturing partners. In this environment, although most of the products and parts are produced in local plants, they can also be purchased from any desirable manufacturing partners at reasonable costs. The objective of this study is to provide efficient integrated production plans for both local plants with finite production capacity and manufacturing partners, while minimizing the total production costs. For solving this problem, we formulated an integrated production planning problem by modifying a multi-level lot-sizing (MLLS) problem, and proposed an efficient genetic-algorithm-based heuristic for minimizing the costs of production, inventory, and subcontracting with manufacturing partners. The proposed heuristic consists of a unique chromosome structure, a chromosome-generation method, and genetic operators. The experimental analysis shows that the proposed heuristic generates quite good solutions at low computational costs, in comparison with a commercial optimization package.

Original languageEnglish
Pages (from-to)547-556
Number of pages10
JournalInternational Journal of Advanced Manufacturing Technology
Volume32
Issue number5-6
DOIs
Publication statusPublished - 2007 Mar 1

Fingerprint

Genetic algorithms
Planning
Chromosomes
Costs

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

Cite this

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Genetic algorithm-based integrated production planning considering manufacturing partners. / Jung, Hosang; Song, Iksoo; Jeong, Bongju.

In: International Journal of Advanced Manufacturing Technology, Vol. 32, No. 5-6, 01.03.2007, p. 547-556.

Research output: Contribution to journalArticle

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