Abstract
Over the past decades, the volume and diversity of municipal solid waste (MSW) generated by the United States have risen significantly. Together with increasing environmental regulations, these pressures have made solid waste management (SWM) a critical issue for communities. SWM systems are highly complex, requiring a variety of facilities and transfer mechanisms. Unlike many large-scale systems, both government agencies and private contractors work cooperatively with sophisticated network relationships in SWM systems. Thus, the characteristics of each facility, as well as uncertainties at both the facility and system levels, must be assessed and quantified prior to modeling. In light of the economic and environmental pressures facing municipalities, the necessity of modeling and optimization for decision support has become apparent. Therefore, a modular simulation and optimization framework is proposed, in which agent-based modeling captures multi-agent interactions and agent-specific objectives, while operation of treatment and disposal facilities are incorporated with discrete-event facility-level sub-models. This framework provides both global and facility performance monitoring and optimization, and has sufficient generality to be applicable to the SWM system of any region, based on database contents. The proposed framework has been successfully applied at both the county and region levels in the State of Florida.
Original language | English |
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Title of host publication | IIE Annual Conference and Expo 2013 |
Publisher | Institute of Industrial Engineers |
Pages | 132-141 |
Number of pages | 10 |
State | Published - Jan 1 2013 |
Event | IIE Annual Conference and Expo 2013 - San Juan, Puerto Rico Duration: May 18 2013 → May 22 2013 |
Other
Other | IIE Annual Conference and Expo 2013 |
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Country/Territory | Puerto Rico |
City | San Juan |
Period | 5/18/13 → 5/22/13 |
Keywords
- Hybrid modeling
- Modeling of large-scale systems
- Modular modeling
- Recycling programs
- Solid waste management
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering