Abstract A new genetic algorithm based on multi-niche crowding is capable of efficiently 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 genetic algorithms to multi-criteria decision making problems. This concept is applied to address the problems arising in the context of remediation of a contaminated aquifer. The multi-niche crowding genetic algorithm is used to decide the optimal location of pumping wells. The aquifer dynamics are simulated by repeatedly solving the partial differential equations describing the flow of water using SUTRA code. Output of this simulation constitutes the input to the genetic algorithm.