In this research, the goal was to develop an agent-based simulation-based decision making and optimization framework for the effective planning of single-stream recycling (SSR) programs. The proposed framework was comprised of two main modules: 1) the simulation module, and 2) the fleet utilities and resource allocation optimization module. The simulation module is where various sources of system uncertainties were parameterized and incorporated into the simulation model of SSR. Alternatives of SSR (i.e., dual-stream recycling (DSR)) with respect to characteristics, cost, environmental impacts, bottleneck facilities, types and capacities of the processing facilities needed, convenience for public participation factors were also evaluated. In the fleet utilities and resources allocation optimization module, a formula for the multi-criteria problem of allocation of limited resources with a view to optimize routing and fleet utilizing aspects was developed. The optimum combination of variables were determined via the embedded genetic algorithm based optimization mechanism for the state of Florida to reach its 75% recycling goal. Here, the optimum solution is considered as the combination of variables which will lead to the highest recycling percentage with minimum cost and maximum benefits. Using this tool, stakeholders are able to test several “what-if” scenarios in their system before reaching a conclusion.

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University of FloridaFlorida international universityUSFMiami UniversityFlorida A&MUCFFlorida StateFAUUniversity of West FloridaFlorida Institute of Technology