Paper Information

Journal:   INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING AND PRODUCTION MANAGEMENT (IJIE) (INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE) (PERSIAN)   WINTER 2007 , Volume 17 , Number 6; Page(s) 67 To 77.
 
Paper: 

A NEURAL APPROACH FOR CONSTRAINT SATISFACTION OF A GENERALIZED JOB SHOP SCHEDULING PROBLEM WITH FUZZY PROCESS TIMES

 
 
Author(s):  TAVAKOLI MOGHADAM R., SAFAEI N.
 
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Abstract: 

This paper presents a fuzzy-neural approach for constraint satisfaction of a generalized job shop scheduling problem (GJSSP) with fuzzy process time. This paper is an extension of recently developed research carried out in the literature. However, we assume that the process time is uncertain. Due to NP-hard nature of the problem, there is a need of using a metaheuristic method.
The first step of any metaheuristic method is to generate initial solutions. Thus, the proposed fuzzy neural approach can adaptively adjust its weights of connections based on the sequence, resource, and uncertain process time constraints of the GJSSP during its processing. Simulations have shown that the proposed fuzzy-neural approach is efficient with respect to the capability of accessing to feasible space and the solution speed.

 
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