Quantum Approaches To the 0/1 Multi-Knapsack Problem: Qubo Formulation, Penalty Parameter Characterization and Analysis
No Thumbnail Available
Date
2025
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Science and Technology Publications, Lda
Open Access Color
Green Open Access
No
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
The 0/1 Multi-Knapsack Problem (MKP) is a combinatorial optimization problem with applications in lo gistics, finance, and resource management. Advances in quantum computing have enabled the exploration of problems like the 0/1 MKP through Quadratic Unconstrained Binary Optimization (QUBO) formulations. This work develops QUBO formulations for the 0/1 MKP, with a focus on optimizing penalty parameters for encoding constraints. Using simulation experiments across quantum platforms, we evaluate the feasibility of solving small-scale instances of the 0/1 MKP. The results provide insights into the challenges and opportuni ties associated with applying quantum optimization methods for constrained resource allocation problems. © 2025 by SCITEPRESS– Science and Technology Publications, Lda.
Description
Keywords
Gate-Based Quantum Computing, Multi-Knapsack Problem, Quadratic Unconstrained Binary Optimization, Quantum Annealing, Quantum Approximate Optimization Algorithm, Quantum Simulation
Turkish CoHE Thesis Center URL
Fields of Science
Citation
WoS Q
N/A
Scopus Q
Q4

OpenCitations Citation Count
N/A
Source
International Conference on Agents and Artificial Intelligence -- 17th International Conference on Agents and Artificial Intelligence, ICAART 2025 -- 23 February 2025 through 25 February 2025 -- Porto -- 328949
Volume
1
Issue
Start Page
815
End Page
823
PlumX Metrics
Citations
Scopus : 0
Google Scholar™

OpenAlex FWCI
0.0
Sustainable Development Goals
11
SUSTAINABLE CITIES AND COMMUNITIES


