A Linked Simulation–Optimization (LSO) Model for Conjunctive Irrigation Management using Clonal Selection Algorithm

Abstract

A Linked Simulation–Optimization (LSO) model based on a Clonal Selection Algorithm (CSA) was formulated for application in conjunctive irrigation management. A series of measures were considered for reducing the computational burden associated with the LSO approach. Certain modifications were incurred to the formulated CSA, so as to decrease the number of function evaluations. In addition, a simple problem specific code for a two dimensional groundwater flow simulation model was developed. The flow model was further simplified by a novel approach of area reduction, in order to save computational time in simulation. The LSO model was applied in the irrigation command of the Pagladiya Dam Project in Assam, India. With a view to evaluate the performance of the CSA, a Genetic Algorithm (GA) was used as a comparison base. The results from the CSA compared well with those from the GA. In fact, the CSA was found to consume less computational time than the GA while converging to the optimal solution, due to the modifications incurred in it.