A Look at Algorithm BEPtoPNST

Juan Carlos García Ojeda
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Abstract

This work analyzes the computational complexity of algorithm BEPtoPNST which transforms a building-evacuation problem (BEP) into a time-ex-panded, process-network synthesis (PNST) problem. The solution of the latter is achieved by resorting to the P-graph method which exploits the combinatorial nature of a BEP. Unlike other approaches, the P-graph method provides not only the optimal solution (best evacuation route as a function of egress time), but also the best n sub-optimal solutions. For the complexity analysis, a generic processor, and a Random-access machine (RAM) model were deployed as well as a mathematical model to calculate the number and cost of the operations performed. It was observed that algorithm BEPtoPNST exhibits an asymptotic complexity of order O ( T | A | (| N | –k)). When solving a BEP, however, the total complexity grows exponentially with order O (T | A | (| N | –k)) + O (2h)) in the worst case; where h represents the total number of operating units specified in the corresponding PNST problem. Nevertheless, the computational comple-xity can be reduced significantly when the P-graph method is deployed.
看看BEPtoPNST算法
本文分析了算法BEPtoPNST的计算复杂性,该算法将建筑物疏散问题(BEP)转化为一个时间扩展的过程网络综合问题(PNST)。后者的求解是通过利用BEP的组合性质的P-图方法来实现的。与其他方法不同,P-图方法不仅提供了最优解(作为出口时间函数的最佳疏散路线),而且还提供了最佳的n个子最优解。为了进行复杂性分析,部署了一个通用处理器和随机存取机(RAM)模型,以及一个数学模型来计算所执行操作的数量和成本。观察到算法BEPtoPNST表现出O阶(T|A|(|N|–k))的渐近复杂度。然而,当求解BEP时,在最坏的情况下,总复杂度随阶O(T|a|(|N|–k))+O(2h)呈指数增长;其中h表示在相应的PNST问题中指定的操作单元的总数。然而,当使用P图方法时,计算复杂性可以显著降低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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