Approximating the longest path length of a stochastic DAG by a normal distribution in linear time

Journal of Discrete Algorithms

Volumn 7, Issue 4, 2009, Pages 420-438

  Ando, Ei ^a   Nakata, Toshio ^b   Yamashita, Masafumi ^a,c  

^a KYUSHU UNIVERSITY   (Japan)

^b FUKUOKA UNIVERSITY OF EDUCATION   (Japan)

^c Fukuoka Industry Academia Symphonicity   (Japan)

Author keywords

Approximation; Directed acyclic graph; Longest path problem; Normal distribution; Stochastic edge weight

Indexed keywords

APPROXIMATION; DELAY ANALYSIS; DIRECTED ACYCLIC GRAPH; DIRECTED ACYCLIC GRAPHS; DISTRIBUTED RANDOM VARIABLES; EDGE LENGTH; LINEAR TIME; LINEAR-TIME ALGORITHMS; LOGICAL CIRCUIT; LONGEST PATH; LONGEST PATH PROBLEM; STOCHASTIC EDGE WEIGHT; TAIL PROBABILITY; TYPICAL APPLICATION; UPPER BOUND; WORST-CASE ANALYSIS;

APPROXIMATION ALGORITHMS; BENCHMARKING; DELAY CIRCUITS; DISTRIBUTION FUNCTIONS; ELECTRIC NETWORK ANALYSIS; LOGIC CIRCUITS; RANDOM PROCESSES; RANDOM VARIABLES;

NORMAL DISTRIBUTION;

EID: 67650278719     PISSN: 15708667     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jda.2009.01.001     Document Type: Article

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