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Resource search is a popular application area of P2P networks and the ant colony algorithm (ACA) is a heuristic approach inspired by the foraging behavior of real ants.
资源搜索是P2P网络应用领域中最为广泛的问题，蚁群算法是受到自然界中真实的蚂蚁集体行为的启发而提出的一种算法。
Ant Colony Algorithm (ACA) is an intelligence-optimized algorithm coming from the illumination of food-seeking behavior by ants based on the shortest route of daumone.
蚁群算法是受自然界蚂蚁觅食过程中，基于信息素的最短路径搜索食物行为启发，提出的一种智能优化算法。
After the basic theory of ACA is introduced, a multiprocessors scheduling policy based on an improved ant colony algorithm is proposed in this paper.
在介绍蚁群算法基本原理以及探讨该算法的缺陷基础上，针对多处理器任务调度问题，提出了一种基于改进型蚁群算法的调度策略。
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