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A unified model framework for the multi-attribute consistent periodic vehicle routing problem.

Maria Gulnara Baldoquin1, Jairo A Martinez1, Jenny Díaz-Ramírez2

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This study introduces a unified model for the periodic vehicle routing problem (PVRP), incorporating multiple real-world constraints. Results highlight the significant impact of objective functions and problem size on solver performance.

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Area of Science:

  • Operations Research
  • Transportation Science
  • Logistics Management

Background:

  • Real-world transportation challenges necessitate integrating various vehicle routing problem (VRP) extensions.
  • The periodic VRP (PVRP) involves multi-day routing with customer-specific visit schedules.
  • Existing models often fail to address multiple PVRP variants concurrently.

Purpose of the Study:

  • To propose a unified modeling framework for the periodic vehicle routing problem (PVRP).
  • To simultaneously incorporate multiple PVRP variants like time-windows, time-dependence, and vehicle consistency.
  • To evaluate the impact of different objective functions on practical PVRP instances.

Main Methods:

  • Developed a unified mathematical model for the periodic vehicle routing problem.
  • Integrated advanced features: time-windows, time-dependence, and visit consistency.
  • Conducted numerical experiments analyzing the performance of a general-purpose MILP solver.

Main Results:

  • The unified PVRP model effectively integrates multiple complex attributes.
  • Solver performance demonstrated higher sensitivity to the choice of objective functions.
  • Problem size significantly influenced the performance and solution quality of the MILP solver.

Conclusions:

  • The proposed unified framework offers a comprehensive approach to complex PVRPs.
  • Objective function selection and problem scale are critical factors for efficient PVRP solving.
  • Further research can explore advanced solution techniques for large-scale, multi-objective PVRPs.