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  • 1TECNALIA, Basque Research and Technology Alliance (BRTA), 48160 Derio, Spain.

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A new benchmark dataset for real-world bin packing problems (BPP) is introduced, featuring complex constraints. This dataset aims to advance quantum computing research by providing a realistic evaluation platform for quantum solvers.

Keywords:
Bin packing problemOperations researchOptimizationQuantum annealerQuantum computing

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Area of Science:

  • Operations Research
  • Computer Science
  • Quantum Computing

Background:

  • Bin packing problems (BPP) are common optimization challenges with real-world applications.
  • Existing benchmarks often lack the complexity and constraints found in practical scenarios.
  • Evaluating quantum algorithms for BPP requires realistic and challenging datasets.

Purpose of the Study:

  • To propose a novel benchmark dataset for real-world bin packing problems.
  • To facilitate the evaluation of quantum solvers for BPP.
  • To encourage further research in quantum computing for optimization problems.

Main Methods:

  • Development of a dataset comprising 12 instances of bin packing problems.
  • Inclusion of real-world constraints: item/bin dimensions, weight restrictions, item affinities, ordering preferences, and load balancing.
  • Creation of a Python script (Q4RealBPP-DataGen) for dataset generation.
  • Design of instances considering current quantum device limitations.

Main Results:

  • A comprehensive benchmark dataset for real-world bin packing problems.
  • A dataset generator script (Q4RealBPP-DataGen) for creating general-purpose benchmarks.
  • Instances range in complexity with 38 to 53 packages.
  • The benchmark addresses practical constraints crucial for industry applications.

Conclusions:

  • The proposed benchmark provides a valuable resource for assessing quantum algorithms on realistic BPP instances.
  • This work bridges the gap between theoretical BPP research and practical quantum computing applications.
  • The dataset and generator will stimulate advancements in quantum optimization for logistics and resource allocation.