Yes / 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.
Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/948 |
Date | January 2001 |
Creators | Dahal, Keshav P., Burt, G.M., McDonald, J.R., Moyes, A. |
Source Sets | Bradford Scholars |
Language | English |
Detected Language | English |
Type | Article |
Rights | © 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. |
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