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Efficient priority rules that explore flexible job shop characteristics for minimizing total tardiness

This paper presents heuristic strategies that exploit characteristics of the Flexible Job Shop (FJS) environment, an extended version of the NP-hard job-shop problem. The FJS involves a set of jobs composed of operations, and each operation must be processed on a machine that can process it. The criterion is the minimization of total tardiness. Initially, characteristics related to the production system flexibility or, more precisely, characteristics related to the machines that can process each operation and the machines' processing times are identified. Therefore, rules that explore these characteristics and foresee future states of the system are proposed. Computational experiments are conducted with 600 instances. Comparisons with rules from the literature show that the best heuristic proposed outperforms the best known rule in approximately 81 percent of instances.

Job shop; Heuristic; Mathematical programming; Production scheduling


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