Dynamic Job Shop Scheduling with Sequence Dependent Routes using PSO

Job shop scheduling (JSS) is a problem which involves an assignment of a set of tasks to the machines in a predefined sequence in order to optimize one or more objectives considering job performance measures of the system. It’s a multi-objective, multi-criteria optimization problem. A job shop environment consists of ‘n’ jobs. Each job has a given machine routine in which some machines could be given a “miss”. The JSS could be considered as a queuing system that consists of machines and jobs where each job demands a specified sequence (routing) on the machines and involves certain amount of processing time. In the dynamic JSSP, the problem size is not fixed. The jobs arrive randomly and addition of each job increases problem size exponentially. The optimal resource scheduling/re-scheduling for a mechanical manufacturing shop in reasonable computational time is achieved using particle Swarm Optimization (PSO). PSO (Particle swarm optimization) is a meta-heuristic method that calculates a combination of the sequence of the jobs yielding the least processing time or the make span (Best completion case) Keywords— DJSSP (Dynamic Job Shop Scheduling Problem), Particle Swarm Optimisation, Meta-heusistic, Optimization.