Appropriate schemata as a novel concept to characterize building blocks are introduced, and then, the traits of appropriate schemata are presented. The effects of building blocks by search operators are analyzed. Henc...Appropriate schemata as a novel concept to characterize building blocks are introduced, and then, the traits of appropriate schemata are presented. The effects of building blocks by search operators are analyzed. Hence, the experiments on RR-8X8 are employed to verify that appropriate schemata construct the building blocks. The validity of appropriate schemata and building blocks from the views of theory and practice is presented.展开更多
针对实际道路路网的一类路径寻优问题,提出了带回退机制的蚁群搜索算法,求解在实际道路路网中完成遍历所有规定节点的一条较优路径。为解决大规模实际道路路网数据量大、蚁群算法收敛速度慢的问题,分别采用Intel Threading Building Blo...针对实际道路路网的一类路径寻优问题,提出了带回退机制的蚁群搜索算法,求解在实际道路路网中完成遍历所有规定节点的一条较优路径。为解决大规模实际道路路网数据量大、蚁群算法收敛速度慢的问题,分别采用Intel Threading Building Blocks(TBB)和Cilk++并行编程模型实现了并行蚁群搜索。与基于WinAPI函数的多线程蚁群算法相比,这两种模型均避免了手动启动线程及识别临界区资源等复杂操作,开发难度降低;在运行效率方面,基于TBB的并行蚁群算法和基于WinAPI的并行蚁群算法效率接近,而基于Cilk++的并行蚁群算法在双核环境下,运行效率和加速比都超过了基于WinAPI的并行蚁群算法。展开更多
文摘Appropriate schemata as a novel concept to characterize building blocks are introduced, and then, the traits of appropriate schemata are presented. The effects of building blocks by search operators are analyzed. Hence, the experiments on RR-8X8 are employed to verify that appropriate schemata construct the building blocks. The validity of appropriate schemata and building blocks from the views of theory and practice is presented.
文摘针对实际道路路网的一类路径寻优问题,提出了带回退机制的蚁群搜索算法,求解在实际道路路网中完成遍历所有规定节点的一条较优路径。为解决大规模实际道路路网数据量大、蚁群算法收敛速度慢的问题,分别采用Intel Threading Building Blocks(TBB)和Cilk++并行编程模型实现了并行蚁群搜索。与基于WinAPI函数的多线程蚁群算法相比,这两种模型均避免了手动启动线程及识别临界区资源等复杂操作,开发难度降低;在运行效率方面,基于TBB的并行蚁群算法和基于WinAPI的并行蚁群算法效率接近,而基于Cilk++的并行蚁群算法在双核环境下,运行效率和加速比都超过了基于WinAPI的并行蚁群算法。
