An algorithm for multi-objective job shop scheduling problem

Scheduling for job shop is very important in both fields of production management and combinatorial optimization. however, it is quite difficult to achieve an optimal solution to this problem with traditional optimizationapproaches owing to the high computational complexity. the combination of several optimization criteria induces additional complexity and new problems. in this paper, we propose a pareto approach tosolve multi-objective job shop scheduling. the objective considered is to minimize the overall completion time (makespan) and total weighted tardiness (twt). an effective simulated annealing algorithm based onproposed approach is presented to solve multi-objective job shop scheduling problems. an external memory of non-dominated solutions is considered to save and update the non-dominated solutions during the problem solving process. the parameters in the proposed algorithm are determined after conducting a pilot study. numerical examples are used to evaluate and study the performance of the proposed algorithm.