Application of Particle Swarm Optimization for Production Scheduling

Production scheduling is an interdisciplinary challenge of addressing optimality criteria such as minimizing makespan, mean flow time, idle machine time, total tardiness, number of tardy jobs, in-process inventory cost, cost of being late. Research till date used various AI techniques, heuristics and metaheuristics to optimize scheduling criteria. If problem size goes on increasing heuristics is not able to give optimal results. The enumerations for finding the probabilities for improving the utilization of resources turn this problem towards NP-Hard. This paper presents comprehensive coverage of PSO application in solving optimization problems in the area of production scheduling. The paper discusses about use of PSO for improvement in the results of optimality criteria.