caa a22 4500 386350302 CHVBK 20180307111827.0 cr unu---uuuuu 161130e198907 xx s 000 0 eng 10.1017/S0269964800001297 doi S0269964800001297 pii (NATIONALLICENCE)cambridge-10.1017/S0269964800001297 Dodin Bajis Graduate School of Management University of California Riverside, California 92521 Approximating the Stochastic Network by its M Shortest Paths [Elektronische Daten] [Bajis Dodin] Given a stochastic activity network in which the length of some or all of the arcs are random variables with known probability distributions. This paper concentrates on identifying the shortest path and the M shortest paths in the network and on using the M paths to identify surrogate stochastic networks which are amenable for deriving analytical solutions. First, it identifies the M shortest paths using a certain form of stochastic dominance. Second, it identifies the M shortest paths by applying the deterministic methods to the network resulting from replacing the random length of every arc by its mean value. The two sets of the M paths are compared with those obtained by Monte Carlo sampling. Finally, the paper investigates how the distributional properties of the shortest path in the surrogate network compare with those of the shortest path in the original stochastic network. Copyright © Cambridge University Press 1989 Probability in the Engineering and Informational Sciences Cambridge University Press 3/3(1989-07), 435-451 0269-9648 3:3<435 1989 3 PES https://doi.org/10.1017/S0269964800001297 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1017/S0269964800001297 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Dodin Bajis Graduate School of Management University of California Riverside, California 92521 NATIONALLICENCE 773 0- Probability in the Engineering and Informational Sciences Cambridge University Press 3/3(1989-07), 435-451 0269-9648 3:3<435 1989 3 PES CC0 http://creativecommons.org/publicdomain/zero/1.0 nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-cambridge