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A case study of scheduling storage tanks using a hybrid genetic algorithm

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4 Author(s)
Dahal, K.P. ; Centre for Electr. Power Eng., Strathclyde Univ., Glasgow, UK ; Burt, Graeme M. ; NcDonald, J.R. ; Moyes, A.

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

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Evolutionary Computation, IEEE Transactions on  (Volume:5 ,  Issue: 3 )