In this paper, we introduce an enhanced version of the "Quantum-inspired Tabu Search Algorithm" (QTS), termed "amplitude-ensemble" QTS (AE-QTS). By utilizing population information, we bring QTS closer to the quantum algorithm -- Glover Search Algorithm, maintaining algorithmic simplicity. AE-QTS is validated against the 0/1 knapsack problem, showing at least a 20% performance boost across all problems and over a 30% efficiency increase in some cases compared to the original QTS. Even with increasingly complex problems, this method consistently outperforms the original QTS.

翻译：本文提出了一种增强版的“量子启发式禁忌搜索算法”（QTS），即“幅度系综”QTS（AE-QTS）。通过利用种群信息，我们将QTS更贴近量子算法——格罗弗搜索算法，同时保持了算法简洁性。AE-QTS在0/1背包问题上进行了验证，所有问题性能至少提升20%，在某些情况下效率相比原始QTS提高超过30%。即使面对日益复杂的问题，该方法也始终优于原始QTS。