2019/03/14 by Mahesh B. Patil, Patil, Mahesh B., M. Naveen Naidu +5
Computer Science · #FOS: Computer and information sciences #Neural and Evolutionary Computing (cs.NE) #cs.NE
paper · pdf · doi:10.48550/arxiv.1903.06127
16 pages, 12 figures
arxiv created 2019/03/14 · arxiv updated 2019/03/15
Application of the multi-objective particle swarm optimisation (MOPSO) algorithm to design of water distribution systems is described. An earlier MOPSO algorithm is augmented with (a) local search, (b) a modified strategy for assigning the leader, and (c) a modified mutation scheme. For one of the benchmark problems described in the literature, the effect of each of the above features on the algorithm performance is demonstrated. The augmented MOPSO algorithm (called MOPSO+) is applied to five benchmark problems, and in each case, it finds non-dominated solutions not reported earlier. In addition, for the purpose of comparing Pareto fronts (sets of non-dominated solutions) obtained by different algorithms, a new criterion is suggested, and its usefulness is pointed out with an example. Finally, some suggestions regarding future research directions are made.