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中文摘要：
借鉴蚁群算法的进化思想，提出一种求解连续空间优化问题的量子蚂蚁算法。该算法主要包括全局搜索、局部搜索和信息素强度更新规则。在全局搜索过程中，利用信息素强度和启发式函数确定蚂蚁移动方向。在局部搜索过程中，提出了基于Delta势阱的量子搜索，以改善寻优性能，加快收敛速率。通过实例验证表明了该算法的有效性。
英文摘要：
This paper proposes a novel algorithm-Quantum-inspired ant algorithm （QAA） for function optimization. It is based on the basic ant algorithm. It contents the global search, local search and the pheromone update. During global search, ants change their search routes by pheromone and the heuristic function. And it will search the best solution by quantum walk which is based on the Delta potential well, during the local search. It will improve the search capability of the algorithm for the best solution and make the convergence quickly. Simulation results show the convergence performance and validity of QAA.
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