Authors : C. Angalaparameswari and M. Sakthivel
Abstract: This study proposes a Gravitational Search enhanced Memetic Algorithm (GSMA) proposed for solving the Water Distribution Network (WDN) problem where the Gravitational Search Algorithm (GSA) will be the main optimizer for exploration capability and the local search method for exploitation is derived from the Simulated Annealing (SA) and Particle Swarm Optimization (PSO) methods. When one technique cannot handle a challenging problem on its own then, its performance can be enhanced by functionally integrated with another technique. Memetic algorithm is one such heuristic model where a meta-heuristic approach is combined with a local search technique. The GSA is proven as an elite method for thorough exploration of the search space. Similarly, SA and PSO methods when integrated and utilized properly with appropriate operators will prove to be a promising local search model. This new memetic algorithm model solves the WDN, a complex real time optimization problem which is NP-hard and requires robust solution techniques for obtaining optimum results. Numerical experiments on three benchmark WDN problems are executed and the result of the proposed GSMA method is compared with the other existing methods for WDN in the literature.
C. Angalaparameswari and M. Sakthivel, 2016. Water Distribution Network Optimization Using a Gravitational Search Enhanced Memetic Algorithm. Asian Journal of Information Technology, 15: 553-562.