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Job Shop Scheduling Problem Using Genetic Algorithms.

Authors :
Habbadi, Sahar
HERROU, Brahim
SEKKAT, Souhail
Source :
Proceedings of the International Conference on Industrial Engineering & Operations Management; 7/26/2022, p3050-3092, 13p
Publication Year :
2022

Abstract

The Job Shop scheduling problem is very widespread considering its utility in the industry. Several researchers have worked on this subject with the aim of optimizing work sequences. This case study provides an overview on genetic algorithms which present a real potential for solving this type of combinatorial problem of job shop scheduling problem. During this study, the application of this method will be done manually in order to understand the procedure and the process of executing programs based on genetic algorithms. It is a problem where the decision analysis must figure strongly along the process because of the numerous choices and allocations of jobs to machines at the right time, in a very specific order and over a given duration. This operation is done at the operational level and research must find an intelligent method to find the best and most optimal combination. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21698767
Database :
Complementary Index
Journal :
Proceedings of the International Conference on Industrial Engineering & Operations Management
Publication Type :
Conference
Accession number :
162467819