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Multi-objective agent-based modeling of single-stream recycling programs

Author

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  • Shi, Xiaoran
  • Thanos, Aristotelis E.
  • Celik, Nurcin

Abstract

In this research, our goal is to develop an agent-based simulation-based decision making framework for the effective planning of single-stream recycling (SSR) programs. The proposed framework is comprised of two main modules: a structured database and a simulation module. The database houses data necessary for simulating the entire solid waste management (SWM) system. The simulation module performs two major tasks. First, it identifies the various sources of system uncertainties and incorporates them into the SSR simulation model. Second, it compares and evaluates the alternatives of SSR (i.e., dual-stream recycling) with respect to cost, bottleneck facilities, and types and capacities of the processing facilities needed. For demonstration purposes, the proposed framework is applied to the state of Florida which has set a goal of reaching a 75% recycling rate by 2020. The proposed framework is a powerful tool that can be used by stakeholders for the evaluation of several “what-if” scenarios in their system before reaching a conclusion and making a decision.

Suggested Citation

  • Shi, Xiaoran & Thanos, Aristotelis E. & Celik, Nurcin, 2014. "Multi-objective agent-based modeling of single-stream recycling programs," Resources, Conservation & Recycling, Elsevier, vol. 92(C), pages 190-205.
    • Handle: RePEc:eee:recore:v:92:y:2014:i:c:p:190-205
    DOI: 10.1016/j.resconrec.2014.07.002
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    References listed on IDEAS

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    1. Chang, Ni-Bin & Wang, S.F., 1997. "A fuzzy goal programming approach for the optimal planning of metropolitan solid waste management systems," European Journal of Operational Research, Elsevier, vol. 99(2), pages 303-321, June.
    2. Rob Aalbers & Herman Vollebergh, 2008. "An economic analysis of mixing wastes," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 39(3), pages 311-330, March.
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    Cited by:

    1. Nakatani, Jun & Konno, Kiyoto & Moriguchi, Yuichi, 2017. "Variability-based optimal design for robust plastic recycling systems," Resources, Conservation & Recycling, Elsevier, vol. 116(C), pages 53-60.

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