Unified particle swarm optimization for tackling operations research problems

We investigate the performance of the recently proposed unified particle swarm optimization algorithm on two categories of operations research problems, namely minimax and integer programming problems. Different variants of the algorithm are employed and compared with established variants of the particle swarm optimization algorithm. Statistical hypothesis testing is performed to justify the significance of the results. Conclusions regarding the ability of the unified particle swarm optimization method to tackle operations research problems as well as on the performance of each variant are derived and discussed.