Hybrid Computational Intelligence Schemes in Complex Domains: An Extended Review
SETN '02 Proceedings of the Second Hellenic Conference on AI: Methods and Applications of Artificial Intelligence
Process industry scheduling optimization using genetic algorithm and mathematical programming
Journal of Intelligent Manufacturing
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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