TCA*-一种时间约束的近似A*搜索算法

B. Wah, Lon-Chan Chu
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引用次数: 9

摘要

作者开发了TCA*,一个问题无关的,时间约束的,近似a *搜索算法族。该算法旨在在固定的时间约束下以最小的代价获得最佳确定的近似程度,其中代价由累积时空积或搜索过程中遇到的最大空间来衡量。只考虑具有允许启发式函数的A*搜索;具有最佳优先策略的分支定界算法就是这种搜索的一个例子。研究了在多项式时间内容易找到可行解的NP-hard组合优化问题。对于所研究的问题,可以观察到,随着近似程度的降低,执行时间、CST积和所需的最大空间都呈指数增长。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TCA*-a time-constrained approximate A* search algorithm
The authors develop TCA*, a family of problem-independent, time-constrained, approximate A* search algorithms. The algorithms are designed to achieve the best ascertained degree of approximation with the minimum cost under a fixed time constraint, where cost is measured by either the cumulative space-time (CST) product or the maximum space encountered during the search. Only A* searches with admissible heuristic functions are considered; a branch-and-bound algorithm with a best-first strategy is an example of such a search. NP-hard combinatorial optimization problems whose feasible solutions can be found easily in polynomial time are studied. For the problems studied, it is observed that the execution time, the CST product and the maximum space required all increase exponentially as the degree of approximation decreases.<>
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