Job Shop Scheduling Using Modified Simulated Annealing Algorithm

Timely and cost factor is increasingly important in today’s global competitive market. The key problem faced by today’s industries are feasible allocation of various jobs to available resources i.e., machines (Scheduling) and optimal utilization of the available resources. Among the various problems in scheduling, the job shop scheduling is the most complicated and requires a large computational effort to solve it. A typical job shop scheduling problem has a set of jobs to be processed in a set of machines, with certain constraints and objective function to be achieved. The most commonly considered objectives are the minimization of make span, minimization of tardiness which leads to minimization of penalty cost, and to maximize machine utilization. Machine shop scheduling can be done using various techniques like standard dispatching rules, heuristic techniques like Simulated annealing, Tabu Search, Genetic algorithm, etc,.here a typical job shop shop scheduling problem is solved using simulated annealing(SA) technique, a heuristic search algorithm. SA is generic neighbourhood search algorithm used to locate optimal solution very nearer to global optimal solution. A software based program is developed in VB platform for a typical job shop problem and test instances were performed over it. Experimental results obtained were further tuned by varying parameters and optimal results were obtained