Solving Constrained Flow-Shop Scheduling Problem through Multistage Fuzzy Binding Approach with Fuzzy Due Dates
Author(s) -
Hamiden Abd El-Wahed Khalifa,
Sultan S. Alodhaibi,
Pavan Kumar
Publication year - 2021
Publication title -
advances in fuzzy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 19
eISSN - 1687-711X
pISSN - 1687-7101
DOI - 10.1155/2021/6697060
Subject(s) - mathematical optimization , fuzzy logic , piecewise , flow shop scheduling , fuzzy number , job shop scheduling , quadratic equation , computer science , scheduling (production processes) , sequence (biology) , fuzzy set operations , interval (graph theory) , quadratic programming , mathematics , fuzzy transportation , defuzzification , fuzzy set , artificial intelligence , schedule , combinatorics , mathematical analysis , geometry , biology , genetics , operating system
This paper deals with constrained multistage machines flow-shop (FS) scheduling model in which processing times, job weights, and break-down machine time are characterized by fuzzy numbers that are piecewise as well as quadratic in nature. Avoiding to convert the model into its crisp, the closed interval approximation for the piecewise quadratic fuzzy numbers is incorporated. The suggested method leads a noncrossing optimal sequence to the considered problem and minimizes the total elapsed time under fuzziness. The proposed approach helps the decision maker to search for applicable solution related to real-world problems and minimizes the total fuzzy elapsed time. A numerical example is provided for the illustration of the suggested methodology.
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