Earliness—tardiness scheduling on uniform parallel machines using simulated annealing and fuzzy logic approach

Abstract

Just-in-time production philosophy has led to the growing interest in scheduling problems considering both earliness and tardiness penalties. This research work considers the uniform parallel machine earliness—tardiness non-common due date sequence-dependent set-up time scheduling problem (UPETNDDSP) for jobs with varying processing times, where the objective is to minimize the sum of the absolute deviations of job completion times from their corresponding due dates. A simulated annealing (SA) —fuzzy logic approach has been proposed to select the optimal weighted earliness—tardiness combinations in a non-identical parallel machine environment. The SA algorithm identifies the best sequences for the different weighted combinations of earliness and tardiness measures for each given set of jobs. Fuzzy logic is then used to select the optimal weighted combination, which satisfies the combined objective function to a larger extent. The performance of the combined objective function and individual objective measure obtained by the proposed SA—fuzzy technique has been compared with the solutions yielded by the genetic algorithm technique known as the genetic algorithm with partially mapped cross-over operator (GA-PMX) and with those of the results reported in literature. The comparison shows that the proposed SA—fuzzy technique outperforms the existing available techniques.