Paper ID: 2311.12867

Amplitude-Ensemble Quantum-Inspired Tabu Search Algorithm for Solving 0/1 Knapsack Problems

Kuo-Chun Tseng, Wei-Chieh Lai, I-Chia Chen, Yun-Hsiang Hsiao, Jr-Yu Chiue, Wei-Chun Huang

In this paper, an improved version of QTS (Quantum-inspired Tabu Search) has been proposed, which enhances the utilization of population information, called "amplitude-ensemble" QTS (AE-QTS). This makes AE-QTS more similar to the real quantum search algorithm, Grover Search Algorithm, in abstract concept, while keeping the simplicity of the algorithm. Later, we demonstrate the AE-QTS on the classical combinatorial optimization 0/1 knapsack problem. Experimental results show that the AE-QTS outperforms other algorithms, including the QTS, by at least an average of 20% in all cases and even by 30% in some cases. Even as the problem complexity increases, the quality of the solutions found by our method remains superior to that of the QTS. These results prove that our method has better search performance.

Submitted: Nov 8, 2023