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Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Published on: July 4, 2007
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Mathematical modeling in municipal solid waste management: case study of Tehran
Mohsen Akbarpour Shirazi1, Reza Samieifard2, Mohammad Ali Abduli2
1Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran.
Summary
This study optimized Tehran's Solid Waste Management System (SWMS) using a linear programming model. The model reduced the number of transfer stations and processing units, improving efficiency.
Area of Science:
- Urban Management
- Environmental Engineering
- Operations Research
Background:
- Solid Waste Management (SWM) is crucial for urban areas, requiring systematic approaches to address environmental concerns.
- Effective SWM is legally recognized as a vital component of urban infrastructure.
- This research focuses on developing an integrated SWM model for metropolises.
Purpose of the Study:
- To design and apply a linear mathematical programming model for integrated Solid Waste Management.
- To optimize the Solid Waste Management System (SWMS) in Tehran.
- To identify potential reductions in infrastructure for improved SWM.
Main Methods:
- A novel linear programming model was developed for integrated SWM.
- The model was implemented using Lingo software.
- Data from Tehran's SWMS, including 22 municipal regions, 11 transfer stations, and 10 processing units, were utilized.
Main Results:
- Application of the linear programming model determined an optimal configuration for Tehran's SWMS.
- The model's execution led to a reduction in the required number of transfer stations from 11 to 10.
- The number of processing units was optimized, decreasing from 10 to 6.
Conclusions:
- The proposed linear programming model offers an effective method for enhancing urban SWMS.
- The model facilitates infrastructure optimization by reducing the number of transfer stations and processing units.
- This approach provides a viable alternative for improving the efficiency and sustainability of metropolitan SWM.
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