Convergence Rate Improvement in Water Distribution Network Optimization Using Fast Messy Genetic Algorithm (FMGA)

Genetic Algorithm as a one of the main evolutionary algorithms has had a most successful role in the water distribution network optimization. This algorithmhas been undergoing many reforms and improved versions are published. A type of genetic algorithms is Fast Messy Genetic Algorithm (FMGA)، that has the ability to increase the convergence rate in solving optimization problems with reducing the length of chromosomes and removing the inefficient genes، meanwhile studying the chromosomes which are not equal in terms of gene strings. In this paper، for evaluation of the FMGA performance in solving water distribution network optimization problems، after the sensitivity analysis and determining the best values of these parameters، two benchmark networks and a real network are analyzed، which are named Two-loop network، the Hanoi network and Jangal City network، respectively، and the results were compared with previous researches. Least-cost in two loop network was estimated after 2880 number of function evaluations that had significant improvements compared to the results of previous researches. In Hanoi network، the minimum cost obtained equal to 6. 045×106 $ that is less than other researchers results are issued so far. After proving the efficiency of algorithm، its performance was shown in design of real Jangal city network according to increasing network size and design constraints.