Solving Flexible Job Shop Scheduling with Multi Objective Approach

In this paper flexible job-shop scheduling problem (fjsp) is studied in the case of optimizing different contradictory objectives consisting of: (1) minimizing makespan, (2) minimizing total workload, and (3) minimizing workload of the most loaded machine. as the problem belongs to the class of np-hard problems, a new hybrid genetic algorithm is proposed to obtain a large set of paretooptimal solutions in a reasonable run time. the algorithm utilizes from a local search heuristic for improving the chance of obtaining more number of global pareto-optimal solutions. the solution method uses from a perturbed global criterion function for guiding the search direction of the hybrid algorithm. computational experiences show that the hybrid algorithm has superior performance in contrast to previous studies.