Binary Particle Swarm Optimization with Crossover Operation for Discrete Optimization

The field of discrete optimization consists of the areas of linear and integer programming, cover problems, knapsack problems, graph theory, network-flow problems, and scheduling. This paper performs an Experiment for discrete Optimization problem with the Hybridization of Binary Particle Swarm Optimization (BPSO) and Genetic Crossover. There are many algorithms Present for solving discrete optimization problem. Both BPSO and GA have shown to be very effective results. Experiment performed on this paper is for the analysis and behavioral study of Hybridized algorithm. We conclude with the results obtained by the performed experiment on standard benchmark functions, and it is found that proposed algorithm gives better results for few standard benchmark functions. General Terms Discrete Optimization, Algorithm.