Solving game theory problems using linear programming and genetic algorithms

Abstract

In this paper, we proposed an efficient genetic algorithm that will be applied to linear programming problems in order to find out the Fittest Chromosomes. This paper aim to find the optimal strategy of game theory in basketball by using genetic algorithms and linear programming as well as the comparison between traditional methods and modern methods being represented in artificial intelligence, Genetic algorithms as applied in this paper. A new method was adopted in finding the optimal game strategy for player (A) and player (B) through the application of linear programming and finding solutions by using (GA) in MATLAB. The final results confirmed the equivalent of linear programming and genetic algorithms as the model was in the linear approach, and in the case of nonlinearity, genetic algorithm will be in favor definitely. The Matlab program in the calculation of the results for great possibility optimization should also be adopted.