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Adaptive Ant Colony Algorithm Used in WSNs Routing for Information Acquisition of Manufacturing Process

机译：WSN路由中用于制造过程信息获取的自适应蚁群算法

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摘要

Ant colony algorithm (ACA) is employed and improved in routing protocol of information acquisition of manufacturing process based on wireless networks. Weighting factor for paths selection is defined as an exponential variable in adaptive ACA. In this way, it prevents the weighting factor from excess increasing or rapid reducing to 0 which results in local optimum. This approach can dynamically adjust paths selection and improve global search ability by optimizing global policy. Adaptive ACA consumes the least time in the process of searching the most optimized paths and searches the shortest paths under the same of iterative loops. Under the same condition of the information heuristic factor and the expected heuristic factor, the algorithm shows good adaptation, realizes the load balancing between paths and resolves the dynamic adjustment problem.
机译：在基于无线网络的制造过程信息获取路由协议中，采用并改进了蚁群算法。用于路径选择的加权因子在自适应ACA中定义为指数变量。以这种方式，它防止了加权因子过度增加或迅速减小到0，这导致局部最优。这种方法可以通过优化全局策略来动态调整路径选择并提高全局搜索能力。自适应ACA在搜索最优化路径和最小迭代路径的过程中花费最少的时间。在信息启发式因子和期望启发式因子相同的条件下，该算法适应性强，实现了路径之间的负载均衡，解决了动态调整问题。

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