Defining parameters for examining effectiveness of genetic algorithm for optimization problems
Rugved Vivek Deolekar · International Conference on Computing for Sustainable Global Development · 2016
Over the years, the optimization problems are solved using the traditional methods. Finding the state space requires extensive knowledge of the problem domain and mathematical computation. Hence traditional techniques proved to be complex for solving many of the optimization problems. Evolutionary algorithms have given a way to minimize these efforts by using concept of genetic algorithms. Genetic Algorithms use the concept of biological evolution and perform directed search. The natural systems have got lot of adaptive processes which must be well understood for designing genetic algorithms. It would help in designing artificial systems software that retains the robustness of natural systems. They are used to deliver proficient, operative techniques for optimization and applications in machine learning. But there is no quantitative criterion possible to evaluate how much effective genetic algorithms are as compared to traditional techniques. Hence, the paper focuses on examining the effectiveness of genetic algorithms for optimization problems and aims at defining the parameters for the same.