International Journal of Industrial Engineering & Production Management

  In this paper, Multi-objective Flexible dynamic Job shop scheduling with maintenance constraints is investigated. In the recent researches the single objective models were assessed. Whereas in competitive conditions, decision makers encountered with simultaneous multi-objective problems that could be conflict with each other. In this research, the objectives are makespan, mean flow time and mean tardiness. These objectives are adaptable to the concept of just-in-time and supply chain management. In real world, machines may be unavailable for various reasons, such as maintenance. In this paper deterministic machine availability as a non-fixed availability is studied. Therefore a mathematical model and improved genetic algorithm with dynamic control parameters that changed through the algorithm is proposed to reducing the probability of early convergence and local optimum. Moreover a heuristic algorithm is proposed to solve maintenance sub-problem. Computational experiments for the three flexibility levels show that the best result of proposed algorithm without maintenance have 3.9%, 4.9% and 4.55% improvement and mean results have 4.9%, 5.33% and 4.6% improvement compared with existing methods. And with considering one, two and three maintenance, the mean of objective function have increased 4.68%, 9.48% and 11.75%. The results show the superiority of the proposed algorithm .