Application of local and global particle swarm optimization algorithms to optimal design and operation of irrigation pumping systems

Abstract

A particle swarm optimization (PSO) algorithm is used in this paper for optimal design and operation of irrigation pumping systems. An irrigation pumping systems design and management model is first introduced and subsequently solved with the newly introduced PSO algorithm. The solution of the model is carried out in two steps. In the first step an exhaustive enumeration is carried out to find all feasible sets of pump combinations able to cope with a given demand curve over the required period. The PSO algorithm is then called in to search for optimal operation of each set. Having solved the operation problem of all feasible sets, the total cost of operation and depreciation of initial investment is calculated for all the sets and the optimal set and the corresponding optimal operating policy is determined. The proposed model is applied to the design and operation of a real-world irrigation pumping system and the results are presented and compared with those of a genetic algorithm. Two global and local versions of the PSO algorithm are used and their efficiencies are compared to each other and that of a genetic algorithm (GA) model. The results indicate that the proposed model in conjunction with the PSO algorithm is a versatile management model for the design and operation of real-world irrigation pumping systems. © 2008 John Wiley & Sons, Ltd.