A Hybridized GA with LP-LP Model for the Management of Confined Groundwater

A novel hybrid methodology is introduced in this paper for the optimal solution of the groundwater management problem. The problem to be addressed is the optimal determination and operation of a predefined number of wells out of a priori known set of potential wells with fixed locations to minimize the pumping cost of utilizing a two-dimensional (2D) confined aquifer under steady-state flow condition. The solution to this problem should satisfy a downstream demand, a lower/upper bound on the pumping rates, and a lower/upper bound on the water level drawdown in the wells. The problem is solved by hybridizing a genetic algorithm (GA) which suggests the candidate configurations for the operational wells and a hybrid linear programming (LP-LP) approach with the duty of finding the optimal operation policy of the candidate wells defined by their pumping rates. Two different codings, namely binary and integer codings, are used for the GA and their performances are compared. The ability of the proposed hybrid method is tested against two benchmark problems: (1) finding the optimal configuration and pumping rates of a predefined number of wells out of potential wells and (2) finding the optimal number, configuration and pumping rates of the operating wells out of potential wells and the results are presented and compared with the available ones showing superior efficiency and effectiveness of the proposed method.