Multi-objective pump scheduling optimisation using evolutionary strategies

Authors:
Benjamín Barán;Christian von Lücken;Aldo Sotelo
Affiliations:
National Computing Centre, National University of Asunción, P.O. Box 1439, San Lorenzo, Paraguay;National Computing Centre, National University of Asunción, P.O. Box 1439, San Lorenzo, Paraguay;National Computing Centre, National University of Asunción, P.O. Box 1439, San Lorenzo, Paraguay
Venue:
Advances in Engineering Software - Special issue on evolutionary optimization of engineering problems
Year:
2005

Citing 7
Cited 5

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Expert Systems with Applications: An International Journal
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Abstract

Multi-objective Evolutionary Algorithms (MOEAs) are used to solve an optimal pump-scheduling problem with four objectives to be minimized: electric energy cost, maintenance cost, maximum power peak, and level variation in a reservoir. Six different MOEAs were implemented and compared. In order to consider hydraulic and technical constraints, a heuristic algorithm was developed and combined with each implemented MOEA. Evaluation of experimental results of a set of metrics shows that the Strength Pareto Evolutionary Algorithm achieves better overall performance than other MOEAs for the parameters considered in the test problem, providing a wide range of optimal pump schedules to chose from.