A Hybrid Algorithms Construction of Hyper-Heuristic for Test Case Prioritization

Zheng Li, Yanzhao Xi, Ruilian Zhao
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引用次数: 3

Abstract

By scheduling algorithms in the low-level algorithm library, the hyper-heuristic algorithm can help to effectively select an appropriate method to deal with hard computational search problems. The hyper-heuristic algorithm usually includes a high-level scheduling layer and a low-level algorithm layer. The high-level strategy layer selects the algorithm for the next scheduling by evaluating the execution effect of the different algorithms in the low-level layer, while the low-level layer includes a variety of different heuristic algorithms which called algorithm library. The concrete hyper-heuristic framework for multi-objective test case prioritization was presented where the 18 multi-objective algorithms were formed in the low-level library. It has been gradually realized that a hybrid algorithm by combining single objective algorithm and multi-objective optimization algorithm is better than the individual. This paper explores the influence of the construction pattern of algorithm library for the hyper-heuristic algorithm by constructing the fusion pattern of different types of algorithms.
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一种用于测试用例优先排序的超启发式混合算法构建
超启发式算法通过对底层算法库中的算法进行调度,可以有效地选择合适的方法来处理难计算搜索问题。超启发式算法通常包括高级调度层和低级算法层。高级策略层通过评估低级层中不同算法的执行效果来选择下一次调度的算法,而低级层则包含各种不同的启发式算法,称为算法库。给出了多目标测试用例优先排序的具体超启发式框架,在底层库中形成了18种多目标算法。人们逐渐认识到,单目标算法和多目标优化算法相结合的混合算法优于单个算法。本文通过构建不同类型算法的融合模式,探讨算法库构建模式对超启发式算法的影响。
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