IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v10y2020i4p2158244020951269.html
   My bibliography  Save this article

A Novel Planning Method of Urban Building Wastes for Environment Protection and Sustainable Development

Author

Listed:
  • Xiao-ping Bai
  • Xiu-weng Wang

Abstract

The building construction wastes seriously polluted the environment; building construction wastes and the recycling of green packaging materials are the important link of environment protection and sustainable development. The building construction wastes have complicated composition. Some of them can be recycled by simply sorting, but most urban building construction wastes require special separation or reprocessing. Therefore, building an efficient and practical building construction wastes multilevel utilization recycling system to resolve the recycling problems of building construction wastes is meaningful. By systematically analyzing the grading recycling system of building construction wastes, this article uses systems engineering, logistics theory, resources recycling science, management science, and other related methods and knowledge to establish a novel nonlinear programming (LP) intelligence planning analysis model for a complex reverse logistics transportation system composed of three-level recycling parts of the building construction wastes, and applies a practical example to propose the solving method of new models based on genetic algorithms and LINGO software. The presented new model and its detailed solving method can help us find the best recycling scheme from urban building construction wastes, and it has great significance for the sustainable development in building construction enterprises.

Suggested Citation

  • Xiao-ping Bai & Xiu-weng Wang, 2020. "A Novel Planning Method of Urban Building Wastes for Environment Protection and Sustainable Development," SAGE Open, , vol. 10(4), pages 21582440209, November.
  • Handle: RePEc:sae:sagope:v:10:y:2020:i:4:p:2158244020951269
    DOI: 10.1177/2158244020951269
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/2158244020951269
    Download Restriction: no

    File URL: https://libkey.io/10.1177/2158244020951269?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
    ---><---

    References listed on IDEAS

    as
    1. Choudhary, Alok & Sarkar, Sagar & Settur, Srikar & Tiwari, M.K., 2015. "A carbon market sensitive optimization model for integrated forward–reverse logistics," International Journal of Production Economics, Elsevier, vol. 164(C), pages 433-444.
    2. Niknejad, A. & Petrovic, D., 2014. "Optimisation of integrated reverse logistics networks with different product recovery routes," European Journal of Operational Research, Elsevier, vol. 238(1), pages 143-154.
    3. Ji-Su Kim & Dong-Ho Lee, 2015. "An integrated approach for collection network design, capacity planning and vehicle routing in reverse logistics," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(1), pages 76-85, January.
    Full references (including those not matched with items on IDEAS)

    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. Kumar, V.N.S.A. & Kumar, V. & Brady, M. & Garza-Reyes, Jose Arturo & Simpson, M., 2017. "Resolving forward-reverse logistics multi-period model using evolutionary algorithms," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 458-469.
    2. Chen, Daqiang & Ignatius, Joshua & Sun, Danzhi & Zhan, Shalei & Zhou, Chenyu & Marra, Marianna & Demirbag, Mehmet, 2019. "Reverse logistics pricing strategy for a green supply chain: A view of customers' environmental awareness," International Journal of Production Economics, Elsevier, vol. 217(C), pages 197-210.
    3. Xuehong Gao, 2019. "A Novel Reverse Logistics Network Design Considering Multi-Level Investments for Facility Reconstruction with Environmental Considerations," Sustainability, MDPI, vol. 11(9), pages 1-22, May.
    4. Zhang, Abraham & Wang, Jason X. & Farooque, Muhammad & Wang, Yulan & Choi, Tsan-Ming, 2021. "Multi-dimensional circular supply chain management: A comparative review of the state-of-the-art practices and research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
    5. Wen-Tso Huang & Cheng-Chang Lu & Jr-Fong Dang, 2021. "Improving the Return Loading Rate Problem in Northwest China Based on the Theory of Constraints," Mathematics, MDPI, vol. 9(12), pages 1-15, June.
    6. Olga Lingaitienė & Aurelija Burinskienė & Vida Davidavičienė, 2022. "Case Study of Municipal Waste and Its Reliance on Reverse Logistics in European Countries," Sustainability, MDPI, vol. 14(3), pages 1-24, February.
    7. Waltho, Cynthia & Elhedhli, Samir & Gzara, Fatma, 2019. "Green supply chain network design: A review focused on policy adoption and emission quantification," International Journal of Production Economics, Elsevier, vol. 208(C), pages 305-318.
    8. Shankar, Ravi & Pathak, Devendra Kumar & Choudhary, Devendra, 2019. "Decarbonizing freight transportation: An integrated EFA-TISM approach to model enablers of dedicated freight corridors," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 85-100.
    9. Ahmad Alshamrani & Dipanjana Sengupta & Amrit Das & Uttam Kumar Bera & Ibrahim M. Hezam & Moddassir Khan Nayeem & Faisal Aqlan, 2023. "Optimal Design of an Eco-Friendly Transportation Network under Uncertain Parameters," Sustainability, MDPI, vol. 15(6), pages 1-26, March.
    10. Ciardiello, F. & Genovese, A. & Simpson, A., 2019. "Pollution responsibility allocation in supply networks: A game-theoretic approach and a case study," International Journal of Production Economics, Elsevier, vol. 217(C), pages 211-217.
    11. Zhang, Yanzi & Berenguer, Gemma & Zhang, Zhi-Hai, 2024. "A subsidized reverse supply chain in the Chinese electronics industry," Omega, Elsevier, vol. 122(C).
    12. Qiang Du & Jiajie Zhou, 2022. "Evolution of Low Carbon Supply Chain Research: A Systematic Bibliometric Analysis," IJERPH, MDPI, vol. 19(23), pages 1-20, November.
    13. Kadambala, Dinesh K. & Subramanian, Nachiappan & Tiwari, Manoj K. & Abdulrahman, Muhammad & Liu, Chang, 2017. "Closed loop supply chain networks: Designs for energy and time value efficiency," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 382-393.
    14. Botang Li & Kaiyuan Liu & Qiong Chen & Yui-yip Lau & Maxim A. Dulebenets, 2023. "A Necessity-Based Optimization Approach for Closed-Loop Logistics Considering Carbon Emission Penalties and Rewards under Uncertainty," Mathematics, MDPI, vol. 11(21), pages 1-29, November.
    15. Christian Scheller & Kerstin Schmidt & Thomas Stefan Spengler, 2021. "Decentralized master production and recycling scheduling of lithium-ion batteries: a techno-economic optimization model," Journal of Business Economics, Springer, vol. 91(2), pages 253-282, March.
    16. Zhou, Xiaoyang & Wei, Xiaoya & Lin, Jun & Tian, Xin & Lev, Benjamin & Wang, Shouyang, 2021. "Supply chain management under carbon taxes: A review and bibliometric analysis," Omega, Elsevier, vol. 98(C).
    17. Utama, Dana Marsetiya & Santoso, Imam & Hendrawan, Yusuf & Dania, Wike Agustin Prima, 2022. "Integrated procurement-production inventory model in supply chain: A systematic review," Operations Research Perspectives, Elsevier, vol. 9(C).
    18. Paweł Nowicki & Marek Ćwiklicki & Piotr Kafel & Janusz Niezgoda & Magdalena Wojnarowska, 2023. "The circular economy and its benefits for pro‐environmental companies," Business Strategy and the Environment, Wiley Blackwell, vol. 32(7), pages 4584-4599, November.
    19. Banguera, Leonardo A. & Sepúlveda, Juan M. & Ternero, Rodrigo & Vargas, Manuel & Vásquez, Óscar C., 2018. "Reverse logistics network design under extended producer responsibility: The case of out-of-use tires in the Gran Santiago city of Chile," International Journal of Production Economics, Elsevier, vol. 205(C), pages 193-200.
    20. Xiao-Hong Liu & Mi-Yuan Shan & Li-Hong Zhang, 2016. "Low-carbon supply chain resources allocation based on quantum chaos neural network algorithm and learning effect," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(1), pages 389-409, August.

    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:sae:sagope:v:10:y:2020:i:4:p:2158244020951269. 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: SAGE Publications (email available below). General contact details of provider: .

    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.