Genetic Algorithm

Creating or preparing Multi-objective formulations are a realistic models for many complex engineering, AI, mathematical and optimization problems etc. Customized genetic algorithms have been expressed as effective to determine best solutions to these problems. In many real-life problems, there are many conflicts to each other towards objective, and mainly by taking single objective to optimizing a particular solution can give unacceptable result with respective to other objective. An inevitable features of Genetic Algorithm are to generate set of solutions for multi objective problem with satisfying objective at acceptance level without dominating to any other solution. Genetic Algorithm is used in maximization as well as minimization of function. This paper tried to show an overview and tutorial is presented how Genetic Algorithm is best to solve the maximization of function for given function. This feature make Genetic Algorithm very unique from traditional genetic algorithms. Roulette-Wheel selection method is adopted to calculate fitness function and other functions