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Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO

M A Hannan1, Mahmuda Akhtar2, R A Begum3

  • 1Dept. of Electrical Power Engineering, Universiti Tenaga Nasional, 43000 Kajang, Selangor, Malaysia.

Waste Management (New York, N.Y.)
|October 29, 2017
PubMed
Summary
This summary is machine-generated.

This study optimizes waste collection routes using a modified particle swarm optimization (PSO) algorithm within a capacitated vehicle-routing problem (CVRP) model. The optimized approach, considering threshold waste level (TWL), significantly reduces costs and environmental impact.

Keywords:
CVRP modelPSORoute optimizationThreshold waste levelWaste collection

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Area of Science:

  • Operations Research
  • Environmental Science
  • Computer Science

Background:

  • Waste collection route optimization is crucial for reducing operational costs and environmental impact.
  • Existing methods often struggle with efficiency and cost-effectiveness in complex urban environments.
  • Significant expenditure is associated with capital, labor, and variable operational costs in waste management.

Purpose of the Study:

  • To propose a modified particle swarm optimization (PSO) algorithm integrated into a capacitated vehicle-routing problem (CVRP) model.
  • To determine optimal waste collection routes and solutions.
  • To reduce socioeconomic and environmental impacts associated with waste collection.

Main Methods:

  • A modified particle swarm optimization (PSO) algorithm was developed and applied to a capacitated vehicle-routing problem (CVRP) model.
  • Threshold waste level (TWL) and scheduling concepts were incorporated into the PSO-based CVRP model.
  • The algorithm was tested using diverse datasets to evaluate its performance.

Main Results:

  • The proposed CVRP model achieved optimal waste collection and route optimization at 70-75% of the threshold waste level (TWL).
  • For one-week scheduling, 70% TWL outperformed considering all nodes, showing improvements in collected waste, distance, efficiency, fuel consumption, and cost.
  • Key performance indicators like travel distance, total waste collected, efficiency, and route tightness were significantly improved.

Conclusions:

  • The modified PSO-based CVRP model offers a valuable tool for efficient waste collection and route optimization.
  • Achieving optimal results at 70-75% TWL demonstrates a practical and effective strategy for waste management.
  • The optimized model contributes to reducing the socioeconomic and environmental footprint of waste collection services.