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A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light...
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Developing an applied algorithm for multi-trip vehicle routing problem with time windows in urban waste collection: A

Erfan Babaee Tirkolaee1,2, Parvin Abbasian3, Mehdi Soltani4

  • 11 Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Islamic Republic of Iran.

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This study optimizes urban waste collection routes using a multi-trip vehicle routing approach with time windows. An efficient simulated annealing algorithm minimizes costs and improves municipal efficiency.

Keywords:
CPLEX solverVehicle routing problemmultiple tripssimulated annealingtime windowsurban waste collection

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Area of Science:

  • Operations Research
  • Environmental Engineering
  • Logistics Management

Background:

  • Urban waste collection is a significant municipal expense with high operating costs.
  • Inefficiencies in waste collection lead to substantial financial burdens for municipalities.
  • Optimizing collection routes can yield considerable savings in municipal expenditure.

Purpose of the Study:

  • To address the multi-trip vehicle routing problem with time windows for urban waste collection.
  • To minimize total costs, including travel, vehicle employment, and time window penalties.
  • To incorporate practical constraints like serving critical locations (e.g., hospitals) within specific timeframes.

Main Methods:

  • Formulation of the multi-trip vehicle routing problem with time windows.
  • Development and application of an efficient simulated annealing (SA) algorithm.
  • Comparison of the SA algorithm's performance against the CPLEX solver.

Main Results:

  • The proposed simulated annealing algorithm demonstrates high performance.
  • The algorithm achieves optimal solutions in a short computational time.
  • The study validates the model through a case study in Iran, presenting optimal policies.

Conclusions:

  • The developed simulated annealing approach effectively solves the complex urban waste collection routing problem.
  • The model provides a practical and cost-effective solution for municipal waste management.
  • The findings offer valuable insights for optimizing urban logistics and reducing operational costs.