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

TL;DR

This paper extends a quantum-classical framework to effectively solve real-world bin packing problems with heterogeneous bins, multiple dimensions, item-bin associations, and delivery priorities, demonstrating its practical applicability.

Contribution

It introduces novel extensions to the Q4RealBPP framework for complex, real-world bin packing scenarios with multiple features and constraints.

Findings

Successfully solved real-world oriented instances

Extended framework to 1D, 2D, and 3D problems

Demonstrated effectiveness with heterogeneous bins and priorities

Abstract

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.