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Multi-objective pump scheduling optimisation using evolutionary strategies

delete2005-01-01
delete140
PRE
AI
B
Benjamı́n Barán
C
Christian von Lücken
A
Aldo Sotelo
DOI：10.1016/j.advengsoft.2004.03.012delete
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Abstract

Abstract

En 中文
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. (C) 2004 Civil-Comp Ltd and Elsevier Ltd. All rights reserved.
Keywords:
pump scheduling
evolutionary computation
genetic algorithms
pareto dominance
multi-objective optimisation
water supply

Journal

Advances in Engineering Software cover
Advances in Engineering Software
IF:
5.7
Papers:
3.3K
Citations:
1.2W

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No organization information available