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Job shop rescheduling using a hybrid artificial immune system and genetic algorithm model


Mohamed Din, Aniza and Ku-Mahamud, Ku Ruhana and Yusof, Yuhanis and Mahmuddin, Massudi (2012) Job shop rescheduling using a hybrid artificial immune system and genetic algorithm model. In: 7th International Conference on Computing and Convergence Technology, 03-05 December 2012, Seoul, Korea.

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Abstract

This paper discusses on developing a hybrid model to tackle the problem of changing environment in the job shop scheduling problem.The main idea is to develop building blocks of partial schedules using the model developed that can be used to provide backup solutions when disturbances occur during production.This model hybridizes genetic algorithm (GA) with artificial immune systems (AIS) techniques to generate these partial schedules.Each partial schedule, also known as antibody, is assigned a fitness value for the selection of final population of best partial schedules. The results of the analysis are compared with previous research. Future works on this study are also discussed.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: component; artificial immune systems; genetic algorithm; job shop scheduling
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: College of Arts and Sciences
Depositing User: Prof. Dr. Ku Ruhana Ku Mahamud
Date Deposited: 10 Jan 2013 01:42
Last Modified: 21 Jan 2013 01:10
URI: http://repo.uum.edu.my/id/eprint/6975

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