A new genetic algorithm for multi-objective optimization in water resource management

A genetic algorithm (GA) based on multi niche crowding (MNC) is capable of locating all the peaks of a multi-modal function. By associating these peaks with the utility accrued from different sets of decision variables, it is possible to extend the use of GAs to multi-criteria decision making. This concept is applied to the remediation of a contaminated aquifer. The MNC GA is used to decide the optimal location of pumping wells. Aquifer dynamics are simulated by solving the partial differential equations describing the flow of water using SUTRA code. Output of this simulation constitutes the input to the GA