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Investigating a Hybrid Metaheuristic For Job Shop Rescheduling

Abdullah, Salwani; Aickelin, Uwe; Burke, Edmund; Din, Aniza; Qu, Rong

Authors

Salwani Abdullah

Uwe Aickelin

Edmund Burke

Aniza Din

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RONG QU rong.qu@nottingham.ac.uk
Associate Professor



Abstract

Previous research has shown that artificial immune systems can be used to produce robust schedules in a manufacturing environment. The main goal is to develop building blocks (antibodies) of partial schedules that can be used to construct backup solutions (antigens) when disturbances occur during production. The building blocks are created based upon underpinning ideas from artificial immune systems and evolved using a genetic algorithm (Phase I). Each partial schedule (antibody) is assigned a fitness value and the best partial schedules are selected to be converted into complete schedules (antigens). We further investigate whether simulated annealing and the great deluge algorithm can improve the results when hybridised with our artificial immune system (Phase II). We use ten fixed solutions as our target and measure how well we cover these specific scenarios.

Citation

Abdullah, S., Aickelin, U., Burke, E., Din, A., & Qu, R. Investigating a Hybrid Metaheuristic For Job Shop Rescheduling

Conference Name Proceedings of the 3rd Australian Conference on Artificial Life (ACAL.07)
Deposit Date Oct 12, 2007
Peer Reviewed Peer Reviewed
Public URL http://eprints.nottingham.ac.uk/id/eprint/572
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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