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Fuzzy Multiobjective Job-Shop Scheduling

  • Masatoshi Sakawa
Chapter
Part of the Operations Research/Computer Science Interfaces Series book series (ORCS, volume 14)

Abstract

In this chapter, by considering the imprecise or fuzzy nature of the data in real-world problems, job-shop scheduling problems with fuzzy processing time and fuzzy due date are formulated. On the basis of the agreement index of fuzzy due date and fuzzy completion time, the formulated fuzzy job-shop scheduling problems are interpreted to maximize the minimum agreement index. Furthermore, multiobjective job-shop scheduling problems with fuzzy due date and fuzzy processing time are formulated as three-objective problems. Having elicited the linear membership functions reflecting the fuzzy goals of the decision maker (DM), the fuzzy decision of Bellman and Zadeh is adopted for combining them. The genetic algorithm introduced in the previous chapter is extended for solving the formulated problems.

Keywords

Simulated Annealing Triangular Fuzzy Number Fuzzy Goal Offspring Individual Agreement Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Masatoshi Sakawa
    • 1
  1. 1.Department of Artificial Complex Systems Engineering, Graduate School of EngineeringHiroshima UniversityHigashi-HiroshimaJapan

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