Optimal management in regulation of adding materials in water distribution systems by multi-population genetic algorithm method

One of the greatest drawbacks of GAs is that they require a high number of function evaluations to achieve convergence. Each function evaluation entails a full extended-period simulation of the system, which is a computationally expensive process. The net result is that GA optimization is time consuming. For a large distribution system a GA optimization run can take up to a few days on a modern personal computer. In the study efficiency of GA operational optimization was improved through a hybrid method which combines the GA method with a hillclimber search strategy. Hill climber strategies complement GAs by being efficient in finding a local optimum two hillclinber strategies, the Hooke and Jeeves and Fibonacci methods, were investigated. The hybrid method proved to be superior to the pure GA in finding a good solution quickly, both when applied to a test problem and to a large existing water distribution system.