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基于宽度优先搜索的路径生成算法 总被引:3,自引:0,他引:3
宽度优先搜索和深度优先搜索是图论中常用的两种搜索算法.两者各有优势,但深度优先搜索算法的效率在低连通度图中会大大降低,这时更适合采用宽度优先搜索算法.本文提出了一种基于宽度优先搜索的路径生成算法,具有较好的时间复杂性和空间复杂性. 相似文献
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极小不可满足子式能够为可满足性模理论(SMT)公式的不可满足的原因提供精确的解释,帮助自动化工具迅速定位错误.针对极小SMT不可满足子式的求解问题,提出了SMT公式搜索树及其3类结点的概念,并给出了不可满足子式、极小不可满足子式与3类结点之间的映射关系.基于这种映射关系,采用宽度优先的搜索策略提出了宽度优先搜索的极小SMT不可满足子式求解算法.基于业界公认的SMT Competition 2007测试集进行实验的结果表明,该算法能够有效地求解极小不可满足子式. 相似文献
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介绍了基于宽度优先搜索算法对菜单的遍历,完成了菜单项以二叉树的形式存入数据表中和对菜单权限的设置,同时以树形控件的形式直观地反映了菜单的层次结构。 相似文献
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求解八数码问题的几种搜索算法比较 总被引:1,自引:0,他引:1
本文针对八数码问题的求解,给出了深度优先搜索、广度优先搜索和启发式搜索之间的算法比较,并得出结论:在通常情况下,采用启发式搜索算法来进行状态空间的搜索更为方便、快捷。 相似文献
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王远敏 《网络安全技术与应用》2022,(3):40-42
在算法的应用中,深度优先搜索算法在图结构的数据类型中有着广泛的应用,本文设置了两个应用场景,一个是信件能否送达问题,一个是不重复打卡夜跑路线的规划问题,这两个问题都与现实生活息息相关.本文通过对这两个问题的详细分析和解决来说明深度优先搜索算法的各种不同使用场合和方法,同时也分析了在解决问题过程中存在的不足. 相似文献
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刑建垒 《电脑编程技巧与维护》2011,(20):42-43,93
介绍了深度优先算法、宽度优先算法、启发式搜索算法3种方法实现8数码问题,分析了3种算法的可采纳性系统的特点,并用MFC编程实现. 相似文献
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本文针对目标移动的模糊搜索问题,提出了独创的模糊搜索机制,并进而提出了模糊启发式搜索算法FMG。文中证明了,在一定的假设下,算法FMGA将最终找到不断移动的目标。 相似文献
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本文针对目标移动的模糊搜索问题,提出了独创的模糊搜索机制,并进而提出了模糊启发式搜索算法FMGA*。文中证明了,在一定的假设下,算法FMGA*将最终找到不断移动的目标 相似文献
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在噪声图象中如何有效地提取边界是图象分析领域中的难点。启发式搜索的方法常常用于提取边界,但是,这种方法由于采用固定的起始点、固定的引导度量以及对图象仅进行一次性搜索,对噪声往往很敏感,为此提出了一种随机启发式搜索算法,该方法随机地选取起始点,并依照引导度量的概率反复地进行随机搜索获得各种可能的边界轨迹,然后进行各搜索轨迹的积累自增强,最后根据自增强积累统计结果获得边界。大量的实验结果证明,在噪声图象中,随机启发式搜索方法可以在提取出有意义边界的同时有效地抑制噪声。 相似文献
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施皓 《数字社区&智能家居》2007,1(3):817-818
本文是用人工智能中的深度优先算法、宽度优先算法、A*算法、SMA*算法来解决N城市旅行商问题。通过解决路径、耗散值、运行时间等数据比较这几个算法在处理该问题上的优劣。 相似文献
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ANGELO MONFROGLIO 《Software》1996,26(3):251-279
Hybrid genetic algorithms are presented that use constrained heuristic search and genetic techniques for the timetabling problem (TP). The TP is an NP-hard problem for which a general polynomial time deterministic algorithm is not known. The paper describes the classification of constraints and the constraint ordering to obtain the minimization of backtracking and the maximization of parallelism. The school timetabling problem is discussed in detail as a case study. The genetic algorithm approach is particularly well suited to this kind of problem, since there exists an easy way to assess a good timetable, but not a well structured automatic technique for constructing it. So, a population of timetables is created that evolves toward the best solution. The evaluation function and the genetic operators are well separated from the domain-specific parts, such as the knowledge of the problem and the heuristics, i.e. from the timetable builder. The present paper illustrates an approach based on the hybridization of constrained heuristic search with novel genetic algorithm techniques. It compares favourably with known programs to solve decision problems under logic constraints. The cost of the new algorithm and the quality of the solutions obtained in significant experiments are reported. 相似文献
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This paper presents an efficient heuristic block-loading algorithm based on multi-layer search for the three-dimensional container loading problem. First, a basic heuristic block-loading algorithm is introduced. This algorithm loads one block, determined by a block selecting algorithm, in one packing phase, according to a fixed strategy, until no blocks are available. Second, the concept of composite block is introduced, the difference between traditional block and composite block being that composite block can contain multiple types of boxes in one block under some restrictions. Third, based on the depth-first search algorithm, a multi-layer search algorithm is developed for determining the selected block in each packing phase, and making this result closer to the optimal solution. Computational results on a classic data set show that the proposed algorithm outperforms the best known algorithm in almost all the test data. 相似文献
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软硬件划分是软硬件协同设计的关键环节,它决定系统中哪些组件由软件实现,哪些由硬件实现。软硬件划分问题已被证明是NP完全问题。将一类软硬件划分问题看作变异的0-1背包问题,在求解背包问题的算法基础上构造出软硬件划分问题的优质启发解。此外,采用禁忌搜索(Tabu Search)算法对求得的启发解进行改进,在软件开销和通信开销满足一定约束的条件下,使得硬件开销尽可能小。实验结果证明,所提算法对当前最新算法的改进最大可达到28%。 相似文献
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Daniel S. Brown Jeffrey Hudack Nathaniel Gemelli Bikramjit Banerjee 《Computational Intelligence》2017,33(3):524-553
We consider an intelligent agent seeking to obtain an item from one of several physical locations, where the cost to obtain the item at each location is stochastic. We study risk‐aware stochastic physical search (RA‐SPS), where both the cost to travel and the cost to obtain the item are taken from the same budget and where the objective is to maximize the probability of success while minimizing the required budget. This type of problem models many task‐planning scenarios, such as space exploration, shopping, or surveillance. In these types of scenarios, the actual cost of completing an objective at a location may only be revealed when an agent physically arrives at the location, and the agent may need to use a single resource to both search for and acquire the item of interest. We present exact and heuristic algorithms for solving RA‐SPS problems on complete metric graphs. We first formulate the problem as mixed integer linear programming problem. We then develop custom branch and bound algorithms that result in a dramatic reduction in computation time. Using these algorithms, we generate empirical insights into the hardness landscape of the RA‐SPS problem and compare the performance of several heuristics. 相似文献
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本文对启发式搜索及其搜索过程,启发式搜索的估价函数和A*算法等作了介绍.提出使用人工智能中的启发式搜索来获取特定的信息,通过估价函数计算,对有用的链接进行遍历,以提高收集信息资源的查全率和查准率. 相似文献
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