Genetic algorithm-based optimization of water resources allocation under drought conditions

Abstract

The efficient allocation of increasingly scarce water resources is a growing challenge worldwide, particularly during times of drought. This paper describes the development and application of an innovative technique to optimize the allocation of raw water supply to the city of London, UK during a period of drought in 2006. Using genetic algorithms, an optimization tool was developed to derive near-optimal operating strategies for the water company's multiple reservoir system for different projected rainfall scenarios and also to test the robustness of drought contingency strategies for operating the reservoirs down to a lower level under a severe drought condition. The project demonstrated that this approach is rigorous yet practical, the optimization technique is robust and effective and that optimal water allocation is an efficient measure to overcome water scarcity under drought conditions and mitigate consequent impacts. The potential application of genetic algorithms to the day to day operation of a complex water resource system represents a step-change in the industry's approach to managing such systems.

Comparison of Transboundary Water Resources Allocation Models Based on Game Theory and Multi-Objective Optimization

“…In recent years, the multi-objective optimization algorithm has had the advantages of obtaining a complete Pareto front at one time, dealing with large-scale search space effectively and high universality, so the multi-objective optimization algorithm is widely used to the solve water resources allocation model based on multi-objective optimization. Rao et al [16] applied a genetic algorithm to solve the water resources allocation model under drought conditions. Reed et al [17] described the evolutionary multi-objective optimization in water resources.…”

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