QUARTERLY PROGRESS REPORT February 1 st, 2012 April 30 th, 2012

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1 QUARTERLY PROGRESS REPORT February 1 st, 2012 April 30 th, 2012 Simulation-Based Optimization for Planning of Effective Waste Reduction, Diversion, and Recycling Programs PRINCIPLE INVESTIGATOR: TEAM MEMBERS: Nurcin Celik, Ph.D. Department of Industrial Engineering, The University of Miami, Coral Gables, FL, USA Telephone: (305) celik@miami.edu Eric D. Antmann, Xiaoran Shi, and Breanna Hayton WORK ACCOMPLISHED DURING THIS REPORTING PERIOD: During this reporting period, data obtained from the experiments designed and carried out during the previous reporting period was analyzed. These experiments covered a case study of Miami- Dade County, Florida, using the simulation-based optimization framework developed during the previous two reporting periods. Conclusions drawn from this analysis were used to prepare recommendations for Miami-Dade County. These recommendations were prepared with the objective of enhancing the recovery rate of recyclables in the most cost effective manner. Furthermore, data from the experiments and observations of the framework s performance were used to design and implement numerous enhancements to the system. These enhancements expand the geographic range, level of detail, adaptability, flexibility and overall performance of the proposed framework. Preliminary builds of the enhanced framework were prepared, and implementation of this framework for a case study of Broward County, Florida, was initiated. Meanwhile, research was carried out on the solid waste management and recycling systems of the remaining 65 counties in Florida. A database was prepared for the application of the enhanced framework on a statewide scale, to be completed during the next reporting period. The enhanced framework (combining monolithic representation of Miami Dade County, and distributed representation of Broward County) is approximately 85% complete and the statewide survey is approximately 30% complete at present. The next phase will include extending these monolithic and distributed representations to other counties in the State of Florida. INFORMATION DISSEMINATION ACTIVITIES: Site Visits and Presentations: The team presented to Southern Waste Systems and Miami Dade County Public Works and Waste Management Department on February 16, Southern Waste Systems and Miami-Dade County provided feedback on their needs, objectives, and concerns from the proposed framework and contributed background data for database and suggestions for further case study development. Team member Eric Antmann presented at the 2012 ACC Meeting of the Minds in Blacksburg, Virginia on March 31, Feedback on Geographic Information System

2 components was used during the enhancement of the proposed framework during this reporting period. Team member Eric Antmann presented at the University of Miami s Research, Creativity, and Innovation Forum on April 11, The project was awarded first place within the Engineering Category. Feedback on logistical and environmental discharge reporting was used during the enhancement of the proposed framework during this reporting period. The team presented at a career development outreach event at West Miami Junior High School. The team worked on and posted an enhanced website describing the project, accessible at Scholarly Publication: Paper was fully accepted for presentation at 2012 Industrial and Systems Engineering Research Conference (ISERC) in Orlando, FL, May, FINAL RESULTS (MIAMI-DADE COUNTY): A continuous-discrete simulation-based model of the present Miami-Dade County solid waste management system has been developed. This model is broadly divided into four operational regions, which simulate the major components of the real system: diversion, transport, disposal, and environmental discharges. The framework also relies on a database of sequences and schedules, which provide the system with an operating infrastructure. Each facility, in addition to the transfer trucks, is represented in the framework as a resource. Each resource is assigned a schedule, which provides a weekly cycle of hours of operation, and capacities, which limit how much material they can process. All resources except for the trucks have two capacities, one of which is reset every 24 hours and represents daily capacity, and another which counts the material inventory at the facility in real time, representing floating capacity. A partial screenshot of the model can be seen in Figure 1. Figure 1: A partial snapshot of our DSWM model

3 During the previous reporting period, a series of experiments were designed and carried out on the proposed framework, which was developed during the two previous reporting periods. These experiments validated the proposed framework and provided a wealth of information on its performance under a wide variety of demands and situations, including rising waste generation, facility expansion and fleet size management. Table 1, below, summarizes the scenarios that were presented to the framework during these experiments. Each scenario was run with separate objectives to maximize recycling and minimize cost, yielding a total of ten final scenarios tested. Table 1: Scenarios presented to experiments Scenario Waste Generation Facility Capacities Transfer Capacity Remark A Current (2010) Infinite Infinite Theoretical and Validation B Current (2010) Current (2010) Current (2010) Current System Validation Current System under Rising Demand C 3% Annual Growth Current (2010) Current (2010) D 3% Annual Growth 10% uprate, one facility at a time E 3% Annual Growth Current (2010) Current (2010) Variable, trucks, 16-tons each Capital Project Simulation Test Fleet Size Optimization Test Data obtained from these experiments provided much insight regarding both the performance of the proposed framework and the case study system, the Miami-Dade County Department of Solid Waste Management (DSWM). Results showed that the framework consistently yielded solutions which met mass balance and capacity limitation constraints, and constituted the optimal or near-optimal combination of system-wide decision variables. The optimal conditions were defined given the objectives, and the framework applied the objectives accurately and consistently. Furthermore, the framework successfully managed rising waste generation, ending with a 38% increase in generation over twelve years. This result indicates that the DSWM system has sufficient capacity to handle significant increases in waste generation. Meanwhile, it presents the capability of the proposed framework in re-allocating limited resources in order to meet new and dynamic challenges. However, as the waste generation simulated in the experiments increased, the degree to which the framework achieved the objectives decreased. Due to the requirement of capacity feasibility, increased demand reduced the number of feasible solutions, and thus the ability to optimize performance. Essentially, by the end of the 12-year runs with rising waste generation, the optimization activity became more of a task in searching for capacity feasibility. The actual tonnage recycled remained largely constant amongst all feasible candidate solutions, resulting in actual decreases in the recyclables recovery rate compared to present, and no significant difference between results from cost-minimizing and recycling-maximizing runs. These findings further corroborate the framework s ability to find feasible solutions under challenging conditions, but also indicate that the current DSWM system lacked sufficient recycling capacity to achieve any substantial increase in recyclables recovery rate under current or future demand, even if cost were no object.

4 Furthermore, when the framework carried out a 10% capacity uprate at facilities, one-at-a-time, and manipulated fleet size, there was no significant change in the results. This outcome validates the capability of the framework to simulate facility changes and manipulate the transfer system, but also indicates that minor changes would not significantly alter the system-wide performance of the DSWM system. Thus, in order to significantly improve system-wide performance from the disposal side, the focus of the experiments, a large capital investment would be necessary, in the form of a new facility or major expansion. Recommendations derived from these findings are summarized and itemized as the following, for increasing the recyclables recovery rate of the DSWM system in the most cost-effective manner. Details of these results will appear in the final annual report. Efforts should be made to help enhance the pre-disposal diversion of recyclables. Introduction of new commercial and institutional recycling programs and increasing the collection frequency of recyclables are examples to those efforts amongst many others. Pre-disposal activities should be preferred rather than the major capital projects on disposal-side operations. Those activities can not only increase the recycling rate at lower cost, but also generate revenue from recycling. Therefore, the recycling market may function properly and the use of the recycled materials may be encouraged. In addition, resource recovery facilities (waste-to-energy plants) should operate efficiently to play a more significant role through the whole waste processing chain. Discouraging solid waste disposal by raising the solid waste collection and tipping fees should temporarily increase revenue from the SWM system. Over time the revenue would return to its approximate original levels, however the fee change should output elevated rates of recycling. The introduction of education on the benefits of environmental protection and resource sustainability into the primary and secondary school systems should promote the concept of recycling within the rising generation. This recycling conscience attitude should encourage an increase in recycling within current households as well as in additional households once the present students become independents. In addition, financial incentives would be beneficial to provide further influences on the residents motivation to participate into the recycling programs. Efforts should continue to improve the ease with which residents can recycle. Additional recycling bins of various sizes should be provided to the residents by the county free of charge. Also, transformation of the collection fleets from multi-compartmental trucks to single compartment trucks seems to be a beneficial option as single compartment trucks are less expensive to purchase, and may improve fleet flexibility due to the versatility of the vehicles. However, a separate study needs to be conducted focusing on fleet management aspects of the system before reaching to a conclusion. PRELIMINARY RESULTS (PHASE II): During the first two reporting periods of this project, a discrete-continuous model of the solid waste management and recycling system in Miami-Dade County, Florida was developed. The model was heavily based on the monolithic organization of this system, in which the vast majority of activities were carried out by a county agency, the Miami-Dade County Department of Solid Waste Management (DSWM). DSWM owned all but two of the major facilities used for MSW processing and carried out the majority of collection and transfer operations. Furthermore, the other contractors who participated in the system could largely be viewed from the perspective

5 of DSWM, in terms of the location of their facilities, materials and volumes received, and fees charged. Hence, the proposed framework developed and tested thus far simulated and optimized the system from a singular, monolithic perspective, based on the presence of a strong central entity. Broward County, like Miami-Dade County, is a densely populated urban and suburban area, and has all common types of SWM facilities, including transfer stations, waste-to-energy plants, material recovery facilities, and landfills. Some of these facilities are operated by county or municipal governments, whereas the majority are owned and operated by private companies, operating as contractors. Each municipality is responsible for contracting with MSW contractors, either publicly or privately owned, for collection, treatment and disposal of its waste stream. The number of private companies working as contractors to various governments, listed below in Table 2, introduces a level of complexity absent in the Miami-Dade County case study. Furthermore, each contractor, as a module of the system, brings its own operational and financial objectives and constraints, which must be satisfied to some extent for the firm to remain in business. In this system, there is no central organizing entity, and thus no acceptable singular perspective for simulation and optimization. These characteristics of Broward County s modular SWM system create additional challenges for accurate simulation and optimization. Since many SWM systems across Florida feature such a decentralized, modular layout, the proposed framework must be able to accurately capture such systems in order to be applied on a state-wide scale. Table 2: Processing and disposal facilities and their operators in Broward County City of Hallandale Transfer Station* Coral Springs Transfer Station* Broward County Central Residential Transfer Station* Transfer Stations Reuter Recycling-TS Monarch Hill Landfill-TS Snyder Park Transfer Station* City of Hollywood Ash Incinerator* South Broward Resource Recovery Facility Waste-to-energy Plants North Broward Resource Recovery Facility Reuter Recycling-MRF Envirocycle Inc. Delta Recycling Pompano South Sun Recycling LLC #1 Sun Recycling LLC #2 Sun Recycling LLC #3 Sun Recycling LLC #7 Sun Recycling LLC #8 Material Recovery Facilities Monarch Hill Landfill-MRF Choice Recycling Services of Broward, Inc. Transfer/Recycling Services Airport Recycling Systems Inc. Delta Recycling Pompano Delta Recycling Davie All County Waste Recycling FSR Hauling

6 Organic Dynamics LLC Atlas-Lox C&D Recycling C&D Disposal Deerfield Beach Recycling and Transfer Southwest Regional Landfill* Landfills Monarch Hill Landfill-LF Represents public facilities owned by the city or county governments of Broward County Proposed Enhanced Hybrid Simulation and Optimization Framework Based on the challenges presented by this highly modular and decentralized SWM system, the framework was expanded to feature a new hybrid agent-discrete simulation and optimization paradigm. Agent-based modeling was selected in order to accurately capture the unique objectives and constraints of each stakeholder to the system, a necessary capability in order to simulate these decentralized systems. Agent-based models are commonly used in social and health modeling, and offer a level of detail and inclusiveness that was not present in the monolithic, discrete-continuous model previously developed. Furthermore, the agent-based model retains the capability to simulate and optimize monolithic systems, such as that of Miami- Dade County, simply by placing the monolithic agency as the only or major agent. Hence, by transitioning to an agent-based paradigm, the variety of systems that can be captured by the framework increases dramatically. However, agent-based models cannot accurately capture inherently discrete unit processes. Many operations encountered at SWM facilities, and during the transfer of wastes and recyclables, such as the arrival and departure of trucks, and incrementing of capacity, cost, environmental, and other factors, are intrinsically discrete events. Thus, the proposed agent-based framework needed to retain the capability to capture discrete events. Therefore, a hybrid topology was selected and developed, in which elements interact in an agent-based model. Meanwhile, a discrete-event sub-model is embedded, which captures agents inherently discrete internal and transfer activities, on a per-ton basis. Such an arrangement offers the best properties of both modeling strategies: the inclusion of agent-specific details and objectives in interactions between agents, and the accuracy of discrete modeling for their internal and transfer activities. Based on the literature reviewed, the proposed hybrid agent-discrete framework is the first of its kind to incorporate discrete event simulation in an agent-based paradigm, and promises levels of performance, accuracy, and inclusiveness not available in any pre-existing solution. This hybrid model will be able to capture all SWM systems present in the State of Florida. Another extension made to framework was the use of a general architecture, in lieu of the casespecific model developed previously. When initialized, the framework screens the database for the parameters of the system under review, and automatically creates the agents and other elements needed to accurately simulate the system of the selected county. Then, the embedded optimization mechanism is applied to these model elements, providing the same level of detail and accuracy found in case-specific models, but with far greater ease of implementation. With this design, the framework can be expanded to a state-wide scale, without the need for custom modeling of the SWM system in each of Florida s 67 counties. Furthermore, this design allows the framework to be applied to new regions or systems by non-technical personnel, simply by providing the relevant data to the database. Based on the literature reviewed, this framework is also the first general, non-case-specific model of solid waste management and recycling to be developed.

7 Therefore, the combination of the new hybrid agent-discrete paradigm and general architecture significantly expand the capabilities of the proposed framework. These enhancements will facilitate its expansion to the entire State of Florida during the upcoming reporting period and offer greater inclusiveness, ease of use, level of detail, flexibility and accuracy. FUTURE WORK: Work for the following three-month period will focus on the further development of the optimization mechanism for the new hybrid agent-discrete solution developed during this period and the validation of the new model and optimization mechanism. The completion of the proposed modular computer based framework will be followed by its application to the case study of the Broward County Solid Waste Management system, for which a series of experiments will be designed and carried out. Results from these experiments will be analyzed and developed into practical recommendations for the SWM system to assist the county in reaching its recycling goal. Information for remaining counties in Florida will be further investigated and the proposed model will be extended to capture the SWM systems in a statewide scale.