Multi-Objective tool to optimize the Water Resources Management using Genetic Algorithm and the Pareto Optimality Concept

This paper examines the development of a multi-objective tool, called ALL_WATER, in optimizing Water Resources Management. The objectives of satisfying demand and reducing costs were taken into consideration while at the same time respecting water salinity requirements and hydraulic constraints. A Multi-Objective Genetic Algorithm (MOGA) and the PARETO optimality concept were used to resolve the formulated problem. The tool developed was used to help optimize the daily management schedule of a real case study in Tunisia. The hydraulic system is made up of three surface water sources, one demand site, two transfer links and three supply links. Within a short computation time, a PARETO front was identified made up of a set of 72 optimal solutions. The modeling approach and the decision-making flexibility, both shown in the case study, prove that the developed tool is able to efficiently identify a set of optimal solutions on a PARETO front. The developed tool will be able to be used for a large variety of water management problems.