Green fuzzy parallel machine scheduling with sequence-dependent setup in the plastic moulding industry

Job scheduling has always been a challenging task for production managers. It is of special importance if it involves multi-objectives and parallel machines. In this research, our direction is largely motivated by the uncertainty emerged in production systems, where processing times of jobs and setup times of machines are not fixed and they are subject to some uncertainties. Our paper presents a mixed-integer goal programming model considering fuzzy approach for parallel machines environments with separable jobs, sequence-dependent setup times and hazardous waste. Two fuzzy objectives are considered in the model to minimise the total tardiness and the total hazardous waste. Since the model is too complex to be solved using exact methods, we proposed a solution method based on genetic algorithm. To set the input parameters of the solution algorithm, Taguchi method is used. The results of the computational experiments indicate that the proposed algorithm is a proficient method and has efficiently found the optimal solutions for both objective functions.