IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v249y2019icp300-315.html
   My bibliography  Save this article

The impact of various carbon reduction policies on green flowshop scheduling

Author

Listed:
  • Foumani, Mehdi
  • Smith-Miles, Kate

Abstract

In this paper we consider, from an environmental policy-maker perspective, how carbon reduction policies impact the economic competitiveness of the manufacturing sector. Specifically, we focus on flowshop scheduling – which typically aims to minimize makespan for purely economic objectives – and consider how three common carbon reduction policies – namely, taxes on emissions, baselines on emissions, and emissions trading schemes – can create competitive green flowshops that balance minimization of makespan and carbon emissions. The goal is to enable policy-makers to understand how to set policies and control parameters to achieve environmental objectives while ensuring global economic competitiveness of industry. We initially present a set of mixed-integer linear programming (MILP) models for flowshop scheduling problems operating in a regulated environment in which each carbon reduction policy is adopted. We then introduce a bi-objective scheduling framework for the corresponding problem to obtain alternative solutions under each policy. These models and their computational results however, are not the main focus of the study, but are presented as a means to demonstrate how green policies co-exist with economic objectives, with policy-makers in control of the balance. To this end, based on financial data from Australia’s carbon emissions profile, we provide a policy-oriented analysis of the models, and some managerial insights into the effect of scheduling strategies on carbon emissions under different reduction policies. These insights offer support to both environmental policy-makers and corporate production and sustainability managers to determine whether it is technically feasible and profitable to replace traditional scheduling strategies with environmentally friendly scheduling strategies.

Suggested Citation

  • Foumani, Mehdi & Smith-Miles, Kate, 2019. "The impact of various carbon reduction policies on green flowshop scheduling," Applied Energy, Elsevier, vol. 249(C), pages 300-315.
  • Handle: RePEc:eee:appene:v:249:y:2019:i:c:p:300-315
    DOI: 10.1016/j.apenergy.2019.04.155
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261919308165
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2019.04.155?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yu, Shiwei & Wei, Yi-Ming & Guo, Haixiang & Ding, Liping, 2014. "Carbon emission coefficient measurement of the coal-to-power energy chain in China," Applied Energy, Elsevier, vol. 114(C), pages 290-300.
    2. Yenisey, Mehmet Mutlu & Yagmahan, Betul, 2014. "Multi-objective permutation flow shop scheduling problem: Literature review, classification and current trends," Omega, Elsevier, vol. 45(C), pages 119-135.
    3. Gahm, Christian & Denz, Florian & Dirr, Martin & Tuma, Axel, 2016. "Energy-efficient scheduling in manufacturing companies: A review and research framework," European Journal of Operational Research, Elsevier, vol. 248(3), pages 744-757.
    4. Fang, Guochang & Tian, Lixin & Liu, Menghe & Fu, Min & Sun, Mei, 2018. "How to optimize the development of carbon trading in China—Enlightenment from evolution rules of the EU carbon price," Applied Energy, Elsevier, vol. 211(C), pages 1039-1049.
    5. Zhu, Zhi-Shuang & Liao, Hua & Cao, Huai-Shu & Wang, Lu & Wei, Yi-Ming & Yan, Jinyue, 2014. "The differences of carbon intensity reduction rate across 89 countries in recent three decades," Applied Energy, Elsevier, vol. 113(C), pages 808-815.
    6. Yuan, Jun & Ng, Szu Hui, 2017. "Emission reduction measures ranking under uncertainty," Applied Energy, Elsevier, vol. 188(C), pages 270-279.
    7. Ding, Jian-Ya & Song, Shiji & Wu, Cheng, 2016. "Carbon-efficient scheduling of flow shops by multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 248(3), pages 758-771.
    8. Fateme Akhoondi & M.M. Lotfi, 2016. "A heuristic algorithm for master production scheduling problem with controllable processing times and scenario-based demands," International Journal of Production Research, Taylor & Francis Journals, vol. 54(12), pages 3659-3676, June.
    9. Jian-Ya Ding & Shiji Song & Jatinder N.D. Gupta & Cheng Wang & Rui Zhang & Cheng Wu, 2016. "New block properties for flowshop scheduling with blocking and their application in an iterated greedy algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4759-4772, August.
    10. Muhammad Shahbaz & Saleheen Khan & Amjad Ali & Mita Bhattacharya, 2017. "The Impact Of Globalization On Co2 Emissions In China," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 62(04), pages 929-957, September.
    11. Chen, Qianqian & Gu, Yu & Tang, Zhiyong & Wei, Wei & Sun, Yuhan, 2018. "Assessment of low-carbon iron and steel production with CO2 recycling and utilization technologies: A case study in China," Applied Energy, Elsevier, vol. 220(C), pages 192-207.
    12. Shao, Changzheng & Ding, Yi & Wang, Jianhui, 2019. "A low-carbon economic dispatch model incorporated with consumption-side emission penalty scheme," Applied Energy, Elsevier, vol. 238(C), pages 1084-1092.
    13. Lee, Cheng F. & Lin, Sue J. & Lewis, Charles & Chang, Yih F., 2007. "Effects of carbon taxes on different industries by fuzzy goal programming: A case study of the petrochemical-related industries, Taiwan," Energy Policy, Elsevier, vol. 35(8), pages 4051-4058, August.
    14. Kan Fang & Nelson Uhan & Fu Zhao & John Sutherland, 2013. "Flow shop scheduling with peak power consumption constraints," Annals of Operations Research, Springer, vol. 206(1), pages 115-145, July.
    15. Yan, Junna & Zhao, Tao & Kang, Jidong, 2016. "Sensitivity analysis of technology and supply change for CO2 emission intensity of energy-intensive industries based on input–output model," Applied Energy, Elsevier, vol. 171(C), pages 456-467.
    16. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Uncertainty and global sensitivity analysis for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 214(C), pages 219-238.
    17. Mansouri, S. Afshin & Aktas, Emel & Besikci, Umut, 2016. "Green scheduling of a two-machine flowshop: Trade-off between makespan and energy consumption," European Journal of Operational Research, Elsevier, vol. 248(3), pages 772-788.
    18. Shijin Wang & Zhanguo Zhu & Kan Fang & Feng Chu & Chengbin Chu, 2018. "Scheduling on a two-machine permutation flow shop under time-of-use electricity tariffs," International Journal of Production Research, Taylor & Francis Journals, vol. 56(9), pages 3173-3187, May.
    19. Fahimnia, Behnam & Sarkis, Joseph & Choudhary, Alok & Eshragh, Ali, 2015. "Tactical supply chain planning under a carbon tax policy scheme: A case study," International Journal of Production Economics, Elsevier, vol. 164(C), pages 206-215.
    20. Vallada, Eva & Ruiz, Rubén & Framinan, Jose M., 2015. "New hard benchmark for flowshop scheduling problems minimising makespan," European Journal of Operational Research, Elsevier, vol. 240(3), pages 666-677.
    21. Gerardo Minella & Rubén Ruiz & Michele Ciavotta, 2008. "A Review and Evaluation of Multiobjective Algorithms for the Flowshop Scheduling Problem," INFORMS Journal on Computing, INFORMS, vol. 20(3), pages 451-471, August.
    22. Zakeri, Atefe & Dehghanian, Farzad & Fahimnia, Behnam & Sarkis, Joseph, 2015. "Carbon pricing versus emissions trading: A supply chain planning perspective," International Journal of Production Economics, Elsevier, vol. 164(C), pages 197-205.
    23. He, Senyu & Yin, Jianhua & Zhang, Bin & Wang, Zhaohua, 2018. "How to upgrade an enterprise’s low-carbon technologies under a carbon tax: The trade-off between tax and upgrade fee," Applied Energy, Elsevier, vol. 227(C), pages 564-573.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ma, Li & Wang, Lingfeng & Liu, Zhaoxi, 2021. "Multi-level trading community formation and hybrid trading network construction in local energy market," Applied Energy, Elsevier, vol. 285(C).
    2. Yue Qi & Weixin Yao & Jiagui Zhu, 2024. "Study on the Selection of Recycling Strategies for the Echelon Utilization of Electric Vehicle Batteries under the Carbon Trading Policy," Sustainability, MDPI, vol. 16(17), pages 1-33, September.
    3. Chen-Yang Cheng & Shih-Wei Lin & Pourya Pourhejazy & Kuo-Ching Ying & Yu-Zhe Lin, 2021. "No-Idle Flowshop Scheduling for Energy-Efficient Production: An Improved Optimization Framework," Mathematics, MDPI, vol. 9(12), pages 1-18, June.
    4. Meng Sun & Xukuo Gao & Jinze Li & Xiaodong Jing, 2022. "Research on Evolutionary Game of Water Environment Governance Behavior from the Perspective of Public Participation," IJERPH, MDPI, vol. 19(22), pages 1-17, November.
    5. Salla Annala & Lurian Klein & Luisa Matos & Sirpa Repo & Olli Kilkki & Arun Narayanan & Samuli Honkapuro, 2021. "Framework to Facilitate Electricity and Flexibility Trading within, to, and from Local Markets," Energies, MDPI, vol. 14(11), pages 1-20, May.
    6. Hongyu He & Yanzhi Zhao & Xiaojun Ma & Zheng-Guo Lv & Ji-Bo Wang, 2023. "Branch-and-Bound and Heuristic Algorithms for Group Scheduling with Due-Date Assignment and Resource Allocation," Mathematics, MDPI, vol. 11(23), pages 1-14, November.
    7. Zhou, Shengchao & Jin, Mingzhou & Du, Ni, 2020. "Energy-efficient scheduling of a single batch processing machine with dynamic job arrival times," Energy, Elsevier, vol. 209(C).
    8. Guokui Wang & Xiaojia Guo & Jinxiu Fu & Qingyue Wei & Linlin Zhang, 2022. "Alternative pathways to CO2 reduction in Gansu province, China," Energy & Environment, , vol. 33(4), pages 809-825, June.
    9. Malladi, Krishna Teja & Sowlati, Taraneh, 2020. "Bi-objective optimization of biomass supply chains considering carbon pricing policies," Applied Energy, Elsevier, vol. 264(C).
    10. Hajo Terbrack & Thorsten Claus & Frank Herrmann, 2021. "Energy-Oriented Production Planning in Industry: A Systematic Literature Review and Classification Scheme," Sustainability, MDPI, vol. 13(23), pages 1-32, December.
    11. Santos, Lucas F. & Costa, Caliane B.B. & Caballero, José A. & Ravagnani, Mauro A.S.S., 2020. "Synthesis and optimization of work and heat exchange networks using an MINLP model with a reduced number of decision variables," Applied Energy, Elsevier, vol. 262(C).
    12. Küfeoğlu, Sinan & Khah Kok Hong, Dennis, 2020. "Emissions performance of electric vehicles: A case study from the United Kingdom," Applied Energy, Elsevier, vol. 260(C).
    13. Wenjie Wang & Guangdong Tian & Gang Yuan & Duc Truong Pham, 2023. "Energy-time tradeoffs for remanufacturing system scheduling using an invasive weed optimization algorithm," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1065-1083, March.
    14. Abdul Latif & S. M. Suhail Hussain & Dulal Chandra Das & Taha Selim Ustun, 2021. "Design and Implementation of Maiden Dual-Level Controller for Ameliorating Frequency Control in a Hybrid Microgrid," Energies, MDPI, vol. 14(9), pages 1-15, April.
    15. Krzysztof Zagrajek & Józef Paska & Łukasz Sosnowski & Konrad Gobosz & Konrad Wróblewski, 2021. "Framework for the Introduction of Vehicle-to-Grid Technology into the Polish Electricity Market," Energies, MDPI, vol. 14(12), pages 1-30, June.
    16. Valentyna Stanytsina & Volodymyr Artemchuk & Olga Bogoslavska & Artur Zaporozhets & Antonina Kalinichenko & Jan Stebila & Valerii Havrysh & Dariusz Suszanowicz, 2022. "Fossil Fuel and Biofuel Boilers in Ukraine: Trends of Changes in Levelized Cost of Heat," Energies, MDPI, vol. 15(19), pages 1-18, September.
    17. Maliyamu Abudureheman & Qingzhe Jiang & Xiucheng Dong & Cong Dong, 2022. "CO 2 Emissions in China: Does the Energy Rebound Matter?," Energies, MDPI, vol. 15(12), pages 1-25, June.
    18. Xiu Cheng & Jiameng Yang & Yumei Jiang & Wenbin Liu & Yang Zhang, 2022. "Determinants of Proactive Low-Carbon Consumption Behaviors: Insights from Urban Residents in Eastern China," IJERPH, MDPI, vol. 19(10), pages 1-15, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alvarez-Meaza, Izaskun & Zarrabeitia-Bilbao, Enara & Rio-Belver, Rosa-María & Garechana-Anacabe, Gaizka, 2021. "Green scheduling to achieve green manufacturing: Pursuing a research agenda by mapping science," Technology in Society, Elsevier, vol. 67(C).
    2. Weiwei Cui & Biao Lu, 2020. "A Bi-Objective Approach to Minimize Makespan and Energy Consumption in Flow Shops with Peak Demand Constraint," Sustainability, MDPI, vol. 12(10), pages 1-22, May.
    3. Zhou, Shengchao & Jin, Mingzhou & Du, Ni, 2020. "Energy-efficient scheduling of a single batch processing machine with dynamic job arrival times," Energy, Elsevier, vol. 209(C).
    4. Deming Lei & Youlian Zheng & Xiuping Guo, 2017. "A shuffled frog-leaping algorithm for flexible job shop scheduling with the consideration of energy consumption," International Journal of Production Research, Taylor & Francis Journals, vol. 55(11), pages 3126-3140, June.
    5. Hajo Terbrack & Thorsten Claus & Frank Herrmann, 2021. "Energy-Oriented Production Planning in Industry: A Systematic Literature Review and Classification Scheme," Sustainability, MDPI, vol. 13(23), pages 1-32, December.
    6. Golpîra, Hêriş, 2020. "Smart Energy-Aware Manufacturing Plant Scheduling under Uncertainty: A Risk-Based Multi-Objective Robust Optimization Approach," Energy, Elsevier, vol. 209(C).
    7. Perez-Gonzalez, Paz & Framinan, Jose M., 2024. "A review and classification on distributed permutation flowshop scheduling problems," European Journal of Operational Research, Elsevier, vol. 312(1), pages 1-21.
    8. Chen-Yang Cheng & Shih-Wei Lin & Pourya Pourhejazy & Kuo-Ching Ying & Yu-Zhe Lin, 2021. "No-Idle Flowshop Scheduling for Energy-Efficient Production: An Improved Optimization Framework," Mathematics, MDPI, vol. 9(12), pages 1-18, June.
    9. Matthias Gerhard Wichmann & Christoph Johannes & Thomas Stefan Spengler, 2019. "An extension of the general lot-sizing and scheduling problem (GLSP) with time-dependent energy prices," Journal of Business Economics, Springer, vol. 89(5), pages 481-514, July.
    10. Anghinolfi, Davide & Paolucci, Massimo & Ronco, Roberto, 2021. "A bi-objective heuristic approach for green identical parallel machine scheduling," European Journal of Operational Research, Elsevier, vol. 289(2), pages 416-434.
    11. Zhi-Fu Mi & Yi-Ming Wei & Chen-Qi He & Hua-Nan Li & Xiao-Chen Yuan & Hua Liao, 2017. "Regional efforts to mitigate climate change in China: a multi-criteria assessment approach," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 22(1), pages 45-66, January.
    12. Catanzaro, Daniele & Pesenti, Raffaele & Ronco, Roberto, 2023. "Job scheduling under Time-of-Use energy tariffs for sustainable manufacturing: a survey," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1091-1109.
    13. Shu-Hong Wang & Ma-Lin Song & Tao Yu, 2019. "Hidden Carbon Emissions, Industrial Clusters, and Structure Optimization in China," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1319-1342, December.
    14. Yang, Yuxiang & Goodarzi, Shadi & Jabbarzadeh, Armin & Fahimnia, Behnam, 2022. "In-house production and outsourcing under different emissions reduction regulations: An equilibrium decision model for global supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    15. Ghorbanzadeh, Masoumeh & Ranjbar, Mohammad, 2023. "Energy-aware production scheduling in the flow shop environment under sequence-dependent setup times, group scheduling and renewable energy constraints," European Journal of Operational Research, Elsevier, vol. 307(2), pages 519-537.
    16. Meng, Xiaoge & Yao, Zhong & Nie, Jiajia & Zhao, Yingxue & Li, Zenglu, 2018. "Low-carbon product selection with carbon tax and competition: Effects of the power structure," International Journal of Production Economics, Elsevier, vol. 200(C), pages 224-230.
    17. Fei Luan & Zongyan Cai & Shuqiang Wu & Shi Qiang Liu & Yixin He, 2019. "Optimizing the Low-Carbon Flexible Job Shop Scheduling Problem with Discrete Whale Optimization Algorithm," Mathematics, MDPI, vol. 7(8), pages 1-17, August.
    18. Li, Jin & Wang, Rui & Li, Haoran & Nie, Yaoyu & Song, Xinke & Li, Mingyu & Shi, Mai & Zheng, Xinzhu & Cai, Wenjia & Wang, Can, 2021. "Unit-level cost-benefit analysis for coal power plants retrofitted with biomass co-firing at a national level by combined GIS and life cycle assessment," Applied Energy, Elsevier, vol. 285(C).
    19. Rezgar FEIZI & Sahar AMIDI & Thais NUNEZ-ROCHA & Isabelle RABAUD, 2022. "Carbon Tax and Emissions Transfer: a Spatial Analysis," LEO Working Papers / DR LEO 2965, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    20. Qianyu Zhao & Boyu Xie & Mengyao Han, 2023. "Unpacking the Sub-Regional Spatial Network of Land-Use Carbon Emissions: The Case of Sichuan Province in China," Land, MDPI, vol. 12(10), pages 1-22, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:249:y:2019:i:c:p:300-315. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.