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This study addresses flexible job shop scheduling problem (FJSP) with fuzzy processing time. The fuzzy or uncertainty of processing time is one of seven characteristics in remanufacturing. A discrete harmony search (DHS) algorithm is proposed for FJSP with fuzzy processing time. The objective is to minimise maximum fuzzy completion time. A simple and effective heuristic rule is proposed to initialise harmony population. Extensive computational experiments are carried out using five benchmark cases with eight instances from remanufacturing. The proposed heuristic rule is evaluated using five benchmark cases. The proposed DHS algorithm is compared to six metaheuristics. The results and comparisons show the effectiveness and efficiency of DHS for solving FJSP with fuzzy processing time. [ABSTRACT FROM PUBLISHER]

The resource constrained scheduling problem has been investigated widely in recent years, and many heuristic algorithms have been applied to solve this problem. In this study, we propose a discrete imperialist competitive algorithm (DICA) to solve a variety of resource-constrained hybrid flowshop scheduling problems with the objective of minimizing the completion time. In the proposed algorithm, we employ a two-phase-based coding mechanism, where a local search method is applied. Then, we combine DICA and simulated annealing algorithm (SA) to improve the performance of the algorithm. In addition, we consider the dynamic allocation of resources in the decoding process. We tested the proposed algorithm based on a randomly generated set of real shop scheduling system instances, as well as numerically analyzing and comparing the proposed algorithm with existing heuristic algorithms to verify its effectiveness. [ABSTRACT FROM AUTHOR]