5th European International Conference on Industrial Engineering and Operations Management

Job Shop Scheduling Problem using Genetic Algorithms

Sahar HABBADI, Herrou Brahim & Souhail SEKKAT
Publisher: IEOM Society International
0 Paper Citations
Track: Artificial Intelligence

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.
Optimization, Metaheuristics, Scheduling, Job Shop Scheduling problem, and Algorithm Genetic.

Published in: 5th European International Conference on Industrial Engineering and Operations Management, Rome, Italy

Publisher: IEOM Society International
Date of Conference: July 26-28, 2022

ISBN: 978-1-7923-9161-3
ISSN/E-ISSN: 2169-8767