ad hoc网络中基于蚁群系统算法(Ant Colony System Algorithms,ACSA)的路由协议已经被广泛地研究,但其中的大部分本质上都属于单径路由协议,使得源 ..
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蚁群系统能够通过自适应调整不断优化算法的性能。
Ant Colony System(ACS) can develop excellent performance via self-adaptive behavior.
为得到最优计划方案，针对搭接网络计划，建立了资源均衡优化的数学模型，并设计了自适应蚁群系统的求解算法与实现过程。
To get the optimum solution for the planning, I construct a model of resource optimization for spliced network planning, and design Adaptive Ant Colony Algorithm to solve it.
将量子群进化算法(QEA)与蚁群系统(acs)进行融合，提出一种新的量子蚁群算法(QACA)。
The algorithm is based on the combination of quantum evolutionary algorithm (QEA) and ant colony system (ACS), a new algorithm, quantum ant colony algorithm (QACA) is proposed.
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