Fuzzy programming for multiobjective job shop scheduling with fuzzy processing time and fuzzy duedate through genetic algorithms

In this paper, by considering the imprecise or fuzzy nature of the data in real-world problems, job shop scheduling with fuzzy processing time and fuzzy duedate is introduced. On the basis of the agreement index of fuzzy duedate and fuzzy completion time, multiobjective fuzzy job shop scheduling pro...

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Vydáno v:European journal of operational research Ročník 120; číslo 2; s. 393 - 407
Hlavní autoři: Sakawa, Masatoshi, Kubota, Ryo
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier B.V 16.01.2000
Elsevier
Elsevier Sequoia S.A
Edice:European Journal of Operational Research
Témata:
Agreement index
Algorithms
Fuzzy completion time
Fuzzy duedate
Fuzzy goals
Fuzzy logic
Fuzzy processing time
Genetic algorithms
Job shop scheduling
Job shops
Operations research
Production scheduling
Studies
Job shop scheduling
Agreement index
Fuzzy goals
Fuzzy completion time
Fuzzy processing time
Fuzzy duedate
Genetic algorithms
ISSN:0377-2217, 1872-6860
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Shrnutí:In this paper, by considering the imprecise or fuzzy nature of the data in real-world problems, job shop scheduling with fuzzy processing time and fuzzy duedate is introduced. On the basis of the agreement index of fuzzy duedate and fuzzy completion time, multiobjective fuzzy job shop scheduling problems are formulated as three-objective ones which not only maximize the minimum agreement index but also maximize the average agreement index and minimize the maximum fuzzy completion time. Having elicited the linear membership functions for the fuzzy goals of the decision maker, we adopt the fuzzy decision of Bellman and Zadeh. By incorporating the concept of similarity among individuals into the genetic algorithms using the Gannt chart, a genetic algorithm which is suitable for solving the formulated problems are proposed. As illustrative numerical examples, both 6×6 and 10×10 three-objective job shop scheduling problems with fuzzy duedate and fuzzy processing time are considered, and the feasibility and effectiveness of the proposed method are demonstrated by comparing with the simulated annealing method.
Bibliografie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:0377-2217
1872-6860
DOI:10.1016/S0377-2217(99)00094-6