Application of Linear Programming - Genetic Algorithm Combination for Urmodi Reservoir Operation

Abstract

The reservoir operation is a challenging task to researchers and water managers. The tempo-spatial variability of rainfall in an area causes uneven distribution of water supply for various requirements. Therefore, researchers are in search of new improved technique that satisfies the requirements to the maximum extent. Linear Programming (LP) is a widely adopted technique for reservoir operation. The evolutionary algorithms (EA) have a specific status in the study of reservoir operation. The attempts are being made to make the reservoir operation technique easy. In view of this, the reduction in time of computation for the determination of reservoir yield is studied in this paper. Linear Programming and Genetic Algorithm (LP-GA) combination are used to compute reservoir yield. Its computation time is compared with the time required for simple GA. It is observed that the LP-GA combination is faster and produces nearly equal results as produced by simple GA. From the present study, it is concluded that the LP-GA can reduce the time of computation in reservoir operation studies. The maximum over year yield from Urmodi Reservoir in Maharashtra, India using LP-GA approach is found to be 187.965MCM at the cost of comparatively lesser duration as compared to simple GA technique.