Multi-objective pump scheduling optimisation using evolutionary strategies
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.
pump scheduling evolutionary computation genetic algorithms pareto dominance multi-objective optimisation water supply