SOLVING A CLASS OF STOCHASTIC MINIMIZATION PROBLEMS
成果类型：
Article
署名作者：
BAILEY, MP
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.42.3.428
发表日期：
1994
页码：
428-438
关键词：
摘要：
This work gives a methodology for analyzing a class of discrete minimization problems with random element weights. The minimum weight solution is shown to be an absorbing state in a Markov chain, while the distribution of weight of the minimum weight element is shown to be of phase type. We then present two-sided bounds for matroids with NBUE distributed weights, as well as for weights with bounded positive hazard rates. We illustrate our method using a realistic military communications problem.