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Updated: Apr 26, 2026
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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
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A closed-loop multi-agent swarm framework for synergistic location-routing optimization in municipal solid waste
Yili Liu1, Zhihong Lin1, Wangrui Dou1
1School of Automobile, Chang'an University, Middle Section of South Second Ring Road, Xi'an, 710064, China.
Journal of Environmental Management
|April 24, 2026
Summary
This study optimizes municipal solid waste collection and transportation using multi-agent swarm modeling and bi-level programming. The integrated approach reduces costs by 10% and enhances urban waste management efficiency.
Area of Science:
- Environmental Engineering
- Operations Research
- Computer Science
Background:
- Waste management faces challenges with diverse vehicle types, complex transport, and fluctuating generation.
- Current systems struggle with dynamic optimization for collection and transportation.
Purpose of the Study:
- To develop a collaborative optimization method for municipal solid waste (MSW) collection and transportation.
- To integrate multi-agent swarm modeling and bi-level programming for synergistic optimization.
Main Methods:
- Constructed a bi-level location-routing model with closed-loop feedback.
- Designed a hybrid algorithm combining genetic algorithm and large neighborhood search.
- Addressed the capacitated vehicle routing problem with time windows.
Main Results:
- A retrofit plan for transfer stations reduced total costs by 10%.
- Optimal cost for new construction was achieved with four transfer stations.
- Scenario simulations analyzed economic and environmental impacts.
Conclusions:
- The method provides tools for dynamic multi-vehicle waste collection and transportation.
- Establishes a multi-agent simulation framework for smart waste management platforms.
- Enhances the efficiency and sustainability of urban solid waste systems.
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