Integrated machine tool selection and operation sequencing with capacity and precedence constraints using genetic algorithm

Chiung Moon, Moonhwan Lee, Yoon Ho Seo, Young Hae Lee

Research output: Contribution to journalArticle

32 Citations (Scopus)


In this paper, an integrated machine tool selection and sequencing model is proposed. The model determines machine visiting sequences for all part types, such that the total production time for the production order is minimized and workloads among machine tools are balanced. The model is formulated as a 0-1 integer programming. To solve the model, a genetic algorithm approach based on a topological sort technique is developed. To demonstrate the efficiency of the proposed GA approach on the integrated machine tool selection and sequencing problem, a number of numerical experiments using various size problems are carried out. The numerical experiments show that the proposed GA approach is efficient to this problems.

Original languageEnglish
Pages (from-to)605-621
Number of pages17
JournalComputers and Industrial Engineering
Issue number3
Publication statusPublished - 2002 Sep 1
Externally publishedYes



  • Genetic algorithm
  • Integrated machine selection
  • Operation sequencing

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Information Systems and Management
  • Industrial and Manufacturing Engineering
  • Applied Mathematics

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