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Robust identical parallel machine scheduling with two-stage time-of-use tariff and not-all-machine option.

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Title: Robust identical parallel machine scheduling with two-stage time-of-use tariff and not-all-machine option.
Authors: Feng, Xin1 (AUTHOR), Peng, Hongjun1 (AUTHOR) penghj@njfu.edu.cn
Source: International Journal of Production Research. Jan2024, Vol. 62 Issue 1/2, p380-403. 24p.
Subjects: Tariff, Scheduling, Machinery, Robust optimization, Energy consumption, Distribution planning
Abstract: Time-of-use (TOU) tariff has been implemented in the manufacturing industry to improve energy efficiency by regulating the electricity imbalance between supply and demand. Besides, not-all-machine (NAM) option is another way of energy-saving by using only a subset of all the available machines. This study investigates a robust identical parallel machine scheduling problem with a two-stage TOU tariff and NAM option. Only interval bounds on job processing times are known. The problem is first formulated into a min–max regret model to maximise the robustness. Based on problem properties, both an iterative relaxation-based exact algorithm and a memetic differential evolution-based heuristic are developed to solve the problem. Computational experiments on 240 randomly generated instances with up to 20 jobs are conducted to evaluate the performance of the developed methods. Besides, 900 large-sized randomly generated instances with up to 150 jobs are tested for sensitivity analysis and to identify managerial insights for achieving energy-efficient schedules. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Robust identical parallel machine scheduling with two-stage time-of-use tariff and not-all-machine option.
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  Data: <searchLink fieldCode="AR" term="%22Feng%2C+Xin%22">Feng, Xin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Peng%2C+Hongjun%22">Peng, Hongjun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> penghj@njfu.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Jan2024, Vol. 62 Issue 1/2, p380-403. 24p.
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  Data: <searchLink fieldCode="DE" term="%22Tariff%22">Tariff</searchLink><br /><searchLink fieldCode="DE" term="%22Scheduling%22">Scheduling</searchLink><br /><searchLink fieldCode="DE" term="%22Machinery%22">Machinery</searchLink><br /><searchLink fieldCode="DE" term="%22Robust+optimization%22">Robust optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Distribution+planning%22">Distribution planning</searchLink>
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  Data: Time-of-use (TOU) tariff has been implemented in the manufacturing industry to improve energy efficiency by regulating the electricity imbalance between supply and demand. Besides, not-all-machine (NAM) option is another way of energy-saving by using only a subset of all the available machines. This study investigates a robust identical parallel machine scheduling problem with a two-stage TOU tariff and NAM option. Only interval bounds on job processing times are known. The problem is first formulated into a min–max regret model to maximise the robustness. Based on problem properties, both an iterative relaxation-based exact algorithm and a memetic differential evolution-based heuristic are developed to solve the problem. Computational experiments on 240 randomly generated instances with up to 20 jobs are conducted to evaluate the performance of the developed methods. Besides, 900 large-sized randomly generated instances with up to 150 jobs are tested for sensitivity analysis and to identify managerial insights for achieving energy-efficient schedules. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1080/00207543.2023.2228922
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      – Code: eng
        Text: English
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        PageCount: 24
        StartPage: 380
    Subjects:
      – SubjectFull: Tariff
        Type: general
      – SubjectFull: Scheduling
        Type: general
      – SubjectFull: Machinery
        Type: general
      – SubjectFull: Robust optimization
        Type: general
      – SubjectFull: Energy consumption
        Type: general
      – SubjectFull: Distribution planning
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      – TitleFull: Robust identical parallel machine scheduling with two-stage time-of-use tariff and not-all-machine option.
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              Text: Jan2024
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              Y: 2024
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