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Memetic Algorithm for Constructing Covering Arrays of Variable Strength Based on Global- Best Harmony Search and Simulated Annealing

机译:基于全局最优和搜索和模拟退火的变强度覆盖阵列构造模因算法

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摘要

Covering Arrays (CA) are mathematical objects widely used in the design of experiments in several areas of knowledge and of most recent application in hardware and software testing. CA construction is a complex task that entails a high run time and high computational load. To date, research has been carried out for constructing optimal CAs using exact methods, algebraic methods, Greedy methods, and metaheuristic-based methods. These latter, including among them Simulated Annealing and Tabu Search, have reported the best results in the literature. Their effectiveness is largely due to the use of local optimization techniques with different neighborhood schemes. Given the excellent results of Global-best Harmony Search (GHS) algorithm in various optimization problems and given that it has not been explored in CA construction, this paper presents a memetic algorithm (GHSSA) using GHS for global search, SA for local search and two neighborhood schemes for the construction of uniform and mixed CAs of different strengths. GHSSA achieved competitive results on comparison with the state of the art and in experimentation did not require the use of supercomputers.
机译:Covering Array(CA)是数学对象,广泛用于实验设计中的一些知识领域,以及最近在硬件和软件测试中的应用。 CA的构建是一项复杂的任务,需要较长的运行时间和较高的计算量。迄今为止,已经进行了研究,以使用精确方法,代数方法,贪婪方法和基于元启发式的方法来构建最佳CA。后者,包括“模拟退火”和“禁忌搜索”,在文献中报告了最好的结果。它们的有效性很大程度上是由于使用了具有不同邻域方案的局部优化技术。鉴于全局最佳和声搜索(GHS)算法在各种优化问题中均取得了优异的效果,并且由于尚未在CA构造中进行探索,本文提出了一种将GHS用于全局搜索,将SA用于局部搜索以及将SA用于局部搜索的模因算法(GHSSA)。构建不同强度的统一和混合CA的两个邻域方案。与现有技术相比,GHSSA获得了竞争性结果,并且在实验中不需要使用超级计算机。

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