A machine learning enhanced multi-start heuristic to efficiently solve a serial-batch scheduling problem
Aykut Uzunoglu,
Christian Gahm,
Axel Tuma
Abstract:Serial-batch scheduling problems are widespread in several industries (e.g., the metal processing industry or industrial 3D printing) and consist of two subproblems that must be solved simultaneously: the grouping of jobs into batches and the sequencing of the created batches. This problem’s NP-hard nature prevents optimally solving large-scale problems; therefore, heuristic solution methods are a common choice to effectively tackle the problem. One of the best-performing heuristics in the literature is the AT… Show more
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