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Updated: Jun 10, 2026
11:53
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
A multiobjective modeling approach to locate multi-compartment containers for urban-sorted waste
Lino Tralhão1, João Coutinho-Rodrigues, Luís Alçada-Almeida
1INESC-Coimbra, Rua Antero Quental 199, 3000-141 Coimbra, Portugal. lmlrt@inescc.pt
Waste Management (New York, N.Y.)
|July 30, 2010
Summary
This study optimizes recycling container placement in cities using a multiobjective programming model. It balances costs, accessibility, and population impact for better urban waste management.
Area of Science:
- Urban Planning
- Environmental Engineering
- Operations Research
Background:
- Urban waste management faces challenges in locating recycling facilities.
- Facility costs and population impacts are key concerns.
Purpose of the Study:
- To develop a mixed-integer, multiobjective programming approach for optimal placement and capacity of recycling facilities.
- To integrate this model into a Geographical Information System (GIS)-based decision support system.
Main Methods:
- A multiobjective optimization model was developed to determine facility locations, capacities, and waste allocation.
- The model considers four objectives: minimizing investment cost, average distance to containers, proximity impact, and distance inconvenience.
- A Geographical Information System (GIS)-based interactive decision support system (IDSS) was utilized.
Main Results:
- The approach was tested in Coimbra, Portugal, generating ten solutions for underground sorted waste containers.
- Trade-offs among objectives were presented to decision-makers using various graphical and tabular formats.
- The study demonstrated the IDSS's capability to assist in complex urban planning decisions.
Conclusions:
- The proposed IDSS effectively aids decision-makers in analyzing complex urban waste management problems.
- A balanced solution optimizing multiple objectives can be identified.
- The system allows for iterative refinement of solutions based on decision-maker preferences.
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