Development intelligence scheduling system for flow shop scheduling problem n-jobs
Yusraini Muharni
Industrial Engineering Department of Engineering Faculty Universitas Sultan Ageng Tirtayasa, Jalan Jend. Sudirman Km 3 Cilegon Banten Indonesia 42435
Abstract
Production scheduling problem is arising when a company need to allocate several jobs into limited resources. The problem is related to sequencing the creation or execution of the product as a whole for a number of available machines. This research focus on developing intelligence scheduling system for flow shop scheduling problem n job m machine by applying both heuristic and metaheuristic approch consists of Longest Processing Time (LPT), Shortest Processing Time (SPT), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). The measure of performance of the scheduling is makespan. The Intelligence Schedulling System was designed using MATLAB software programming. The System is tested in Flow Shop Scheduling Problem with configuration of 5 Jobs and 7 Machines. The result shows that the either heuristic approach and metaheuristic approach can run smoothly when solving the scheduling problem in the system.
Keywords: FlowShop;Scheduling;PSO;ACO;Makespan
Topic: Industrial Engineering