Considering environmental impacts in flexible assembly job shop scheduling: non-dominated sorting memetic algorithm

This paper studies the flexible assembly job shop scheduling problems with cleaner production criterion, interruption, and batch delivery. In this case, considering release time, the parts are produced in the first stage in a flexible job shop environment. In the second stage, they are assembled in the flowshop environment to produce the final products. After assembling, in the final stage, the products are sent to customers in batches. The objective function is to minimize the costs of tardiness, earliness, delivery, and maximum completion time, along with minimizing the amount of speed increase and carbon dioxide emissions. To make the problem more realistic, the fuzzy uncertainty is considered in the problem so that the cost of delivery and the amount of carbon dioxide emission are considered as a triangular fuzzy number. In this study, a mixed-integer nonlinear programming model has been developed to solve the used Epsilon-constraint method. Since the problem of flexible job shop scheduling is one of the most complex problems of combinatorial optimization, to solve it, a hybrid algorithm consisting of NSGAII and memetic is presented. To evaluate the performance of the proposed algorithm, according to some evaluation criteria, the proposed algorithm and NSGAII were compared, and the obtained results showed that the proposed algorithm has good performance.