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

K. Dahal, J.R. McDonald, G.M. Burt, A.J. Moyes

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)283-294
Number of pages11
JournalIEEE Transactions on Evolutionary Computation
Issue number3
Publication statusPublished - 2001


  • genetic algorithms
  • process control
  • scheduling
  • water treatment
  • power systems


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