A Case Study of Scheduling Storage Tanks Using a Hybrid Genetic Algorithm
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2001Rights
© 2001 IEEE. Reprinted from IEEE Transactions on Evolutionary Computation. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bradford's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.Peer-Reviewed
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This paper proposes the application of a hybrid genetic algorithm (GA) for scheduling storage tanks. The proposed approach integrates GAs and heuristic rule-based techniques, decomposing the complex mixed-integer optimization problem into integer and real-number subproblems. The GA string considers the integer problem and the heuristic approach solves the real-number problems within the GA framework. The algorithm is demonstrated for three test scenarios of a water treatment facility at a port and has been found to be robust and to give a significantly better schedule than those generated using a random search and a heuristic-based approach.Citation
Dahal, K.P., Burt, G.M., McDonald, J.R. and Moyes, A. (2001). A Case Study of Scheduling Storage Tanks Using a Hybrid Genetic Algorithm. IEEE Transactions on Evolutionary Computation. Vol. 5, No. 3, pp. 283-294.Link to Version of Record
https://doi.org/10.1109/4235.930316Type
Articleae974a485f413a2113503eed53cd6c53
https://doi.org/10.1109/4235.930316