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Flexible Job-Shop Scheduling Integrating Carbon Cap-And-Trade Policy and Outsourcing Strategy

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  • Like Zhang

    (Henan Provincial Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, Zhengzhou 450002, China)

  • Wenpu Liu

    (Henan Provincial Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, Zhengzhou 450002, China)

  • Hua Wang

    (College of Mechanical and Power Engineering, Nanjing Tech University, Nanjing 211816, China)

  • Guoqiang Shi

    (College of Mechanical and Power Engineering, Nanjing Tech University, Nanjing 211816, China)

  • Qianwang Deng

    (State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082, China)

  • Xinyu Yang

    (Henan Provincial Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, Zhengzhou 450002, China)

Abstract

Carbon cap-and-trade is a practical policy in guiding manufacturers to produce economic and environmental production plans. However, previous studies on carbon cap-and-trade are from a macro level to guide manufacturers to make production plans, rather than from a perspective of specific production scheduling, which leads to a lack of theoretical guidance for manufacturers to develop reasonable production scheduling schemes for specific production orders. This article investigates a specific scheduling problem in a flexible job-shop environment that considers the carbon cap-and-trade policy, aiming to provide guidance for specific production scheduling (i.e., resource allocation). In the proposed problem, carbon emissions have an upper limit. A penalty will be generated if the emissions overpass the predetermined cap. To satisfy the carbon emission cap, the manufacturer can trade carbon credits or adopt outsourcing strategy, that is, outsourcing partial orders to partners at the expense of outsourcing costs. To solve the proposed model, a novel and efficient memetic algorithm (NEMA) is proposed. An initialization method and four local search operators are developed to enhance the search ability. Numerous experiments are conducted and the results validate that NEMA is a superior algorithm in both solution quality and efficiency.

Suggested Citation

  • Like Zhang & Wenpu Liu & Hua Wang & Guoqiang Shi & Qianwang Deng & Xinyu Yang, 2025. "Flexible Job-Shop Scheduling Integrating Carbon Cap-And-Trade Policy and Outsourcing Strategy," Sustainability, MDPI, vol. 17(15), pages 1-23, July.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:15:p:6978-:d:1714713
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