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Benchmark dataset for the Asymmetric and Clustered Vehicle Routing Problem with Simultaneous Pickup and Deliveries,

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A new benchmark dataset for the Asymmetric and Clustered Vehicle Routing Problem with Simultaneous Pickup and Deliveries, Variable Costs and Forbidden Paths (AC-VRP-SPDVCFP) is introduced. This dataset, based on real Spanish geography, aids in solving complex logistics challenges.

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Area of Science:

  • Operations Research
  • Logistics Management
  • Computational Optimization

Background:

  • The Vehicle Routing Problem (VRP) is a fundamental challenge in logistics.
  • Real-world distribution problems often involve complex constraints like simultaneous pickups/deliveries, variable costs, and restricted routes.
  • Existing benchmarks may not fully capture the intricacies of problems like newspaper distribution with recycling.

Purpose of the Study:

  • To introduce a novel benchmark dataset for the Asymmetric and Clustered Vehicle Routing Problem with Simultaneous Pickup and Deliveries, Variable Costs and Forbidden Paths (AC-VRP-SPDVCFP).
  • To provide a realistic dataset based on actual geographical data for improved VRP research.
  • To facilitate the development and testing of algorithms for complex, multi-attribute VRP variants.

Main Methods:

  • The creation of 15 benchmark instances for the AC-VRP-SPDVCFP.
  • Utilizing real geographical data from the province of Bizkaia, Spain.
  • The dataset is designed to extend previous work on VRP with recycling policies.

Main Results:

  • A comprehensive benchmark dataset for AC-VRP-SPDVCFP is now available.
  • The dataset comprises instances with 50-100 nodes, reflecting realistic scales.
  • It is based on actual geographic locations, enhancing its applicability.

Conclusions:

  • The presented benchmark dataset offers a valuable resource for researchers in vehicle routing and logistics optimization.
  • It enables more accurate modeling and solving of real-world distribution problems, including those with recycling considerations.
  • The dataset is publicly accessible for further research and development.