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Using a Genetic Algorithm to Solve a Bi-Objective WWTP Process Optimization

In: Operations Research Proceedings 2010

Author

Listed:
  • Lino Costa

    (University of Minho)

  • Isabel A. C. P. Espírito Santo

    (University of Minho)

  • Edite M. G. P. Fernandes

    (University of Minho)

Abstract

When modeling an activated sludge system of a wastewater treatment plant (WWTP), several conflicting objectives may arise. The proposed formulation is a highly constrained bi-objective problem where the minimization of the investment and operation costs and the maximization of the quality of the effluent are simultaneously optimized. These two conflicting objectives give rise to a set of Pareto optimal solutions, reflecting different compromises between the objectives. Population based algorithms are particularly suitable to tackle multi-objective problems since they can, in principle, find multiple widely different approximations to the Pareto-optimal solutions in a single run. In this work, the formulated problem is solved through an elitist multi-objective genetic algorithm coupled with a constrained tournament technique. Several trade-offs between objectives are obtained through the optimization process. The direct visualization of the trade-offs through a Pareto curve assists the decision maker in the selection of crucial design and operation variables. The experimental results are promising, with physical meaning and highlight the advantages of using a multi-objective approach.

Suggested Citation

  • Lino Costa & Isabel A. C. P. Espírito Santo & Edite M. G. P. Fernandes, 2011. "Using a Genetic Algorithm to Solve a Bi-Objective WWTP Process Optimization," Operations Research Proceedings, in: Bo Hu & Karl Morasch & Stefan Pickl & Markus Siegle (ed.), Operations Research Proceedings 2010, pages 359-364, Springer.
    • Handle: RePEc:spr:oprchp:978-3-642-20009-0_57
    DOI: 10.1007/978-3-642-20009-0_57
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