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On the effect of population size and selection mechanism from the viewpoint of collaboration between exploration and exploitation

机译：勘探与开发合作视角下的人口规模与选择机制效应

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摘要

The synergy between exploration and exploitation has been a prominent issue in optimization. Optimization algorithms are generally required to have their parameters tuned to achieve successful exploration-exploitation synergies. Nonetheless, while many algorithms have achieved remarkable success in a wide range of applications, the key to successful exploration-exploitation synergies still remains obscure because conclusions drawn from empirical results or theoretical derivations are usually algorithm specific and/or problem dependent. In our previous studies, a theoretical model based on the concept of local search zones was proposed to provide an alternative perspective depicting the synergy between global search and local search in memetic algorithms. In the present work, we adopt the concept of local search zones to interpret and discuss the effect of population size and selection mechanism, two common design concerns in evolutionary algorithms, on the synergy between exploration and exploitation. In addition to providing interpretations to the effect of population size and selection mechanism on different problem types, this investigation also suggests that with proper mapping, the concept of local search zones is also applicable to delineate the behavior of optimization algorithms with different mechanisms.
机译：勘探与开发之间的协同作用一直是优化中的突出问题。通常需要优化算法来调整其参数，以实现成功的勘探开发协同作用。尽管如此，尽管许多算法在广泛的应用中都取得了显著成功，但成功的勘探与开发协同作用的关键仍然不清楚，因为从经验结果或理论推论得出的结论通常是特定于算法和/或取决于问题的。在我们以前的研究中，提出了一种基于局部搜索区域概念的理论模型，以提供一个替代的视角来描述模因算法中全局搜索和局部搜索之间的协同作用。在当前的工作中，我们采用局部搜索区的概念来解释和讨论种群大小和选择机制（这是进化算法中的两个常见设计问题）对勘探与开发之间协同作用的影响。除了提供对人口规模和选择机制对不同问题类型的影响的解释外，该研究还表明，通过适当的映射，局部搜索区域的概念也适用于描述具有不同机制的优化算法的行为。

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