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New single machine scheduling with nonnegative inventory constraints and discretely controllable processing times

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Abstract

This paper investigates a new single machine scheduling problem (SMSP) featuring nonnegative inventory constraints and discretely controllable processing times. Each job contains a single category of item, and the processing of a job would release a predefined number of items into the terminal inventory of the job. A schedule is to properly specify the job and processing time in each operation for minimizing terminal inventories. An exact algorithm and a hybrid metaheuristic are established to solve the problems with different scales. Computational results indicate that the scheduling approaches are effective and efficient in solving the proposed SMSP.

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Acknowledgements

This research is supported by the National Natural Science Foundation of China under the Grant 71471135.

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  1. School of Mechanical Engineering, Tongji University, Shanghai, 201804, China

    Binghai Zhou & Tao Peng

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  1. Binghai Zhou
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  2. Tao Peng
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Correspondence to Binghai Zhou.

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Zhou, B., Peng, T. New single machine scheduling with nonnegative inventory constraints and discretely controllable processing times. Optim Lett 13, 1111–1142 (2019). https://doi.org/10.1007/s11590-019-01407-y

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