A multi-objective pigeon inspired optimization algorithm for fuzzy production scheduling problem considering mould maintenance

Abstract

The fuzzy production scheduling problem considering mould maintenance (FPSP-MM) is studied. The processing time and the maintenance time are represented by triangular fuzzy numbers. When tasks are executed based on the sequence provided by the fuzzy schedule, the real duration of each task needs to be known so the posteriori solution with deterministic processing times can be obtained. Therefore, the concept of the schedule robustness needs to be considered for the fuzzy problem. The robustness is considered as the optimization objective except for the fuzzy makespan in this research. To optimize these two objective functions, a multi-objective pigeon inspired optimization (MOPIO) algorithm is developed. To extend the pigeon inspired optimization (PIO) algorithm from the single-objective case to the multi-objective case, non-dominated solutions are used as candidates for the leader pigeon designation and a special crowding distance is used to ensure a good distribution of solutions in both the objective space and the corresponding decision space. Furthermore, an index-based ring topology is used to manage the convergence speed. Numerical experiments on a variety of simulated scenarios show the excellent efficiency and effectiveness of the proposed MOPIO algorithm by comparing it with other algorithms.