Abstract
This study considers the NP-hard problem of scheduling jobs on a single-machine against common due dates with respect to earliness and tardiness penalties. An effective and efficient recovering beam search (RBS) algorithm is proposed to solve this problem. To validate and verify the developed algorithm, computational experiments are conducted on a well-known benchmark problem set, and the results are compared with nine meta-heuristics from the relevant literature. The experimental comparison results reveal that the proposed RBS algorithm is a state-of-the-art approach to the single-machine scheduling problem with earliness and tardiness penalties. In terms of both solution quality and computational effort, this study successfully develops a near-optimal approach that will hopefully encourage practitioners to apply it to real-world problems.
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