SCHEDULING OF MACHINES AND AGV’S IN FMS WITH OPERATIONAL CONCLUSION TIME CRITERION BY USING GENETIC PARTICLE SWARM ALGORITHM

This paper addresses the scheduling of equipment (machines) and automated pallets without driver (AGV) in an extremely computerized industrialized system (FMS) with objectives to reduce the prepared conclusion time. The scheduling optimization is carried out using Hybrid Meta Heuristic Algorithm (GA-PSO). An enlarge in the concert of the FMS under deliberation would be predictable as a result of making the scheduling of AGVs and machines an essential part of the overall scheduling movements. Intended for this particular problem, develop a code in JAVA which gives most favorable succession with operational conclusion time for ten job sets and four layouts. The algorithm is veteran by means of problems generated by different authors and the conclusion time is obtained by existing algorithm is compared with that obtained by other authors and analyzed.