Authors: Linus Ekstrom, Hao Wang, Sebastian Schmitt

Published on: December 21, 2023

Impact Score: 8.22

Arxiv code: Arxiv:2312.14151

Summary

• What is new: The introduction of a variational quantum multiple-objective optimization (QMOO) algorithm designed for NISQ computers to tackle multi-objective optimization problems.
• Why this is important: Existing research primarily focuses on single-objective optimization problems, neglecting the complexity of real-world issues that involve multiple conflicting objectives.
• What the research proposes: A variational quantum algorithm that leverages a variational quantum circuit (VQC) to generate a quantum state representing a superposition of Pareto-optimal solutions, effectively addressing multiple-objective optimization challenges.
• Results: Successful application of the algorithm on several benchmark problems with up to five objectives demonstrates its effectiveness.

Technical Details

Technological frameworks used: NISQ-compliant variational quantum circuits

Models used: Variational quantum multiple-objective optimization (QMOO)

Data used: Benchmark problems with up to five objectives

Potential Impact

Companies in logistics, finance, and any sector requiring complex decision-making could greatly benefit or need to adapt due to this quantum optimization technology.

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