A robust scheduling method based on a multi-objective immune algorithm
A robust scheduling method based on a multi-objective immune algorithm
A robust scheduling method is proposed to solve uncertain scheduling problems. An uncertain scheduling problem is modeled by a set of workflow models, and then a scheduling scheme (solution) of the problem can be evaluated by workflow simulations executed with the workflow models in the set.
A multi-objective immune algorithm is presented to find Pareto optimal robust scheduling schemes that have good performance for each model in the set. The two optimization objectives for scheduling schemes are the indices of the optimality and robustness of the scheduling results.
An antibody represents a resource allocation scheme, and the methods of antibody coding and decoding are designed to deal with resource conflicts during workflow simulations. Experimental tests show that the proposed method can generate a robust scheduling scheme that is insensitive to uncertain scheduling environments.
production scheduling, workflow model, immune algorithm, variable neighborhood, multi-objective optimization
3359-3369
Zuo, Xingquan
7375efd3-75cb-4d7c-baa7-0fd932257c64
Mo, Hongwei
20f61e6f-6b6a-4f8e-a61b-5e65614b9082
Wu, Jianping
db314ad9-d011-4c77-9ae1-b190f82fd013
9 September 2009
Zuo, Xingquan
7375efd3-75cb-4d7c-baa7-0fd932257c64
Mo, Hongwei
20f61e6f-6b6a-4f8e-a61b-5e65614b9082
Wu, Jianping
db314ad9-d011-4c77-9ae1-b190f82fd013
Zuo, Xingquan, Mo, Hongwei and Wu, Jianping
(2009)
A robust scheduling method based on a multi-objective immune algorithm.
Information Sciences, 179 (19), .
(doi:10.1016/j.ins.2009.06.003).
Abstract
A robust scheduling method is proposed to solve uncertain scheduling problems. An uncertain scheduling problem is modeled by a set of workflow models, and then a scheduling scheme (solution) of the problem can be evaluated by workflow simulations executed with the workflow models in the set.
A multi-objective immune algorithm is presented to find Pareto optimal robust scheduling schemes that have good performance for each model in the set. The two optimization objectives for scheduling schemes are the indices of the optimality and robustness of the scheduling results.
An antibody represents a resource allocation scheme, and the methods of antibody coding and decoding are designed to deal with resource conflicts during workflow simulations. Experimental tests show that the proposed method can generate a robust scheduling scheme that is insensitive to uncertain scheduling environments.
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Published date: 9 September 2009
Keywords:
production scheduling, workflow model, immune algorithm, variable neighborhood, multi-objective optimization
Identifiers
Local EPrints ID: 73817
URI: http://eprints.soton.ac.uk/id/eprint/73817
ISSN: 0020-0255
PURE UUID: 4d46e40b-5d23-46ae-9f6f-306a95324a94
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Date deposited: 11 Mar 2010
Last modified: 13 Mar 2024 22:18
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Contributors
Author:
Xingquan Zuo
Author:
Hongwei Mo
Author:
Jianping Wu
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