An artificial immune system for solving production scheduling problems: a review

Authors:
Ahmad Shahrizal Muhamad;Safaai Deris
Affiliations:
Artificial Intelligence and Bioinformatics Group, Faculty of Computer Science and Information System, Universiti Teknologi Malaysia, UTM Skudai, Malaysia 81310;Artificial Intelligence and Bioinformatics Group, Faculty of Computer Science and Information System, Universiti Teknologi Malaysia, UTM Skudai, Malaysia 81310
Venue:
Artificial Intelligence Review
Year:
2013

Citing 13
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Generating robust and flexible job shop schedules using genetic algorithms

IEEE Transactions on Evolutionary Computation

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Abstract

This article reviews the production scheduling problems focusing on those related to flexible job-shop scheduling. Job-shop and flexible job-shop scheduling problems are one of the most frequently encountered and hardest to optimize. This article begins with a review of the job-shop and flexible job-shop scheduling problem, and follow by the literature on artificial immune systems (AIS) and suggests ways them in solving job-shop and flexible job-shop scheduling problems. For the purposes of this study, AIS is defined as a computational system based on metaphors borrowed from the biological immune system. This article also, summarizes the direction of current research and suggests areas that might most profitably be given further scholarly attention.