Comparison of Memetic Algorithm and PSO in Optimizing Multi Job Shop Scheduling

This study proposes a memetic algorithm to optimize multi objective multi job shop scheduling problems. It consists of customized genetic algorithm and local search of steepest ascent hill climbing algorithm. In genetic algorithm, the customization is done on genetic operators so that new selection crossover and mutation operators have been proposed. The experimental study has been done on benchmark multi job shop scheduling problem and its versatility is proved by comparing its performance with the results of simple genetic algorithm and particle swarm optimization.