mlsanityData to 7 Oct 2026

Solving Logistic-Oriented Bin Packing Problems Through a Hybrid Quantum-Classical Approach

arXiv 2308.02787 ↗First posted 5 Aug 2023cs.AI cs.ET quant-phcited by 2

Not on the map. Why?

Abstract (arXiv)

The Bin Packing Problem is a classic problem with wide industrial applicability. In fact, the efficient packing of items into bins is one of the toughest challenges in many logistic corporations and is a critical issue for reducing storage costs or improving vehicle space allocation. In this work, we resort to our previously published quantum-classical framework known as Q4RealBPP, and elaborate on the solving of real-world oriented instances of the Bin Packing Problem. With this purpose, this paper gravitates on the following characteristics: i) the existence of heterogeneous bins, ii) the extension of the framework to solve not only three-dimensional, but also one- and two-dimensional instances of the problem, iii) requirements for item-bin associations, and iv) delivery priorities. All these features have been tested in this paper, as well as the ability of Q4RealBPP to solve real-world oriented instances.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 4 of its 40 references that are in the map. First posted on arXiv 5 Aug 2023.

Builds on

4 of 40 references.

References · 4

  1. 2017Solving a New 3D Bin Packing Problem with Deep Reinforcement Learning Methodcited by 30
  2. 2020Quantum computing for energy systems optimization: Challenges and opportunitiescited by 15
  3. 2023Hybrid Approach for Solving Real-World Bin Packing Problem Instances Using Quantum Annealerscited by 7
  4. 2023Benchmark dataset and instance generator for Real-World Three-Dimensional Bin Packing Problemscited by 1

Built on by

Cited by year

Citing papers per year: 2024: 1; 2025: 1.

2 papers.