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A web-based decision support system for waste lube oils collection and recycling

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  • Repoussis, P.P.
  • Paraskevopoulos, D.C.
  • Zobolas, G.
  • Tarantilis, C.D.
  • Ioannou, G.

Abstract

This paper presents a web-based decision support system (DSS) that enables schedulers to tackle reverse supply chain management problems interactively. The focus is on the efficient and effective management of waste lube oils collection and recycling operations. The emphasis is given on the systemic dimensions and modular architecture of the proposed DSS. The latter incorporates intra- and inter-city vehicle routing with real-life operational constraints using shortest path and sophisticated hybrid metaheuristic algorithms. It is also integrated with an Enterprise Resource Planning system allowing the utilization of particular functional modules and the combination with other peripheral planning tools. Furthermore, the proposed DSS provides a framework for on-line monitoring and reporting to all stages of the waste collection processes. The system is developed using a web architecture that enables sharing of information and algorithms among multiple sites, along with wireless telecommunication facilities. The application to an industrial environment showed improved productivity and competitiveness, indicating its applicability on realistic reverse logistical planning problems.

Suggested Citation

  • Repoussis, P.P. & Paraskevopoulos, D.C. & Zobolas, G. & Tarantilis, C.D. & Ioannou, G., 2009. "A web-based decision support system for waste lube oils collection and recycling," European Journal of Operational Research, Elsevier, vol. 195(3), pages 676-700, June.
    • Handle: RePEc:eee:ejores:v:195:y:2009:i:3:p:676-700
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    Cited by:

    1. Liu, Ran & Jiang, Zhibin, 2012. "The close–open mixed vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 220(2), pages 349-360.
    2. Habjan Andreja, 2023. "How a Perceived Utilisation of IT-enabled Information shapes Customer Satisfaction in B2B arkets," Business Systems Research, Sciendo, vol. 14(2), pages 81-101, December.
    3. Aksen, Deniz & Kaya, Onur & Sibel Salman, F. & Tüncel, Özge, 2014. "An adaptive large neighborhood search algorithm for a selective and periodic inventory routing problem," European Journal of Operational Research, Elsevier, vol. 239(2), pages 413-426.
    4. Yong Xie & Hongwei Wang, 2014. "A Group Cooperative Decision Support System Based on Extended Contract Net," Group Decision and Negotiation, Springer, vol. 23(5), pages 1191-1217, September.
    5. 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).
    6. Gunasekaran, Angappa & Ngai, Eric W.T., 2012. "The future of operations management: An outlook and analysis," International Journal of Production Economics, Elsevier, vol. 135(2), pages 687-701.
    7. Gamberini, Rita & Gebennini, Elisa & Manzini, Riccardo & Ziveri, Andrea, 2010. "On the integration of planning and environmental impact assessment for a WEEE transportation network—A case study," Resources, Conservation & Recycling, Elsevier, vol. 54(11), pages 937-951.
    8. Olmez, Omer Berk & Gultekin, Ceren & Balcik, Burcu & Ekici, Ali & Özener, Okan Örsan, 2022. "A variable neighborhood search based matheuristic for a waste cooking oil collection network design problem," European Journal of Operational Research, Elsevier, vol. 302(1), pages 187-202.
    9. Guo, Xiaolong & Li, Xiansen & Bian, Junsong & Yang, Chenchen, 2023. "Deposit or reward: Express packaging recycling for online retailing platforms," Omega, Elsevier, vol. 117(C).

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