A Genetic Algorithm and Pattern Search Comparison for Hydro Power Plant Optimization

Abstract

Optimization means finding the best solution for a function by maximizing or minimizing the function value with considering the function constraints. The objective functions that are used in engineering optimization are so complex in nature also has many variables and constraints. Genetic algorithm, Pattern search, Particle swarms, fuzzy etc. are very useful methods in finding global minimum solution related to engineering problem. This paper aims to make a comparison between two optimizations methods, by optimizing a multi-objective function with two variables and subjected to a specific constraints. The two methods used in the comparison are Pattern search and Genetic algorithm to reach to the final conclusion with the help of a case study.