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引用次数: 0
摘要
本研究应用布谷鸟搜索元启发式模型寻找定向运动问题(OP)的解。OP公式对于某人想要确定受特定时间约束的最优城市路线的情况进行建模是有用的。OP可以归类为NP- Hard Problem,即随着涉及实体数量的增加,需要很长时间才能解析出最优解。因此,元启发式通常成为处理这种情况的一种选择。本研究提出了一种基于布谷鸟搜索模型的算法。采用二元布谷鸟搜索的思想,对离散组合问题进行了调整。此外,为了提高搜索性能,还考虑了三种局部搜索方法。该算法最终可以在18种情况中找到比其他两种基准算法更好的解决方案。此外,对模型参数的实验表明,较差的巢状分数(Pα)会影响得到的解的质量。
An Application of Binary Cuckoo Search Algorithm to Orienteering Problem
—This research applies the cuckoo search meta- heuristics model to find solutions to the Orienteering Problem (OP). The OP formulation is useful to model a situation in which someone wants to determine an optimal city route that is subject to a specified time constraint. OP can be categorized into NP- Hard Problem which takes a very long time to analytically find the optimal solution as the number of entities involved increases. Therefore, metaheuristics often become an option to deal with this situation. A cuckoo search model based algorithm is developed in this research. An adjustment for discrete combinatorial problem is performed by adopting an idea of binary cuckoo search method. In addition, three types of local search methods are considered to improve the searching performance. This algorithm can eventually find better solutions for some of the 18 cases than two other benchmarked algorithms. Furthermore, experiment on model parameters shows that the worse nest fraction ( Pα ) affects the quality of solutions obtained.