Models and algorithm for stochastic shortest path problem | |
Ji, XY | |
2010-05-06 ; 2010-05-06 | |
关键词 | shortest path problem genetic algorithm hybrid intelligent algorithms stochastic simulation NETWORKS GRAPHS Mathematics, Applied |
中文摘要 | In this paper, we study the shortest path problem with stochastic arc length. According to different decision criteria, we originally propose the concepts of expected shortest path, a-shortest path and the most shortest path, and present three new types of models: expected value model, chance-con strained programming and dependent-chance programming. In order to solve these models, a hybrid intelligent algorithm integrating stochastic simulation and genetic algorithm is developed and some numerical examples are given to illustrate its effectiveness. (c) 2005 Elsevier Inc. All rights reserved. |
语种 | 英语 ; 英语 |
出版者 | ELSEVIER SCIENCE INC ; NEW YORK ; 360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA |
内容类型 | 期刊论文 |
源URL | [http://hdl.handle.net/123456789/14292] ![]() |
专题 | 清华大学 |
推荐引用方式 GB/T 7714 | Ji, XY. Models and algorithm for stochastic shortest path problem[J],2010, 2010. |
APA | Ji, XY.(2010).Models and algorithm for stochastic shortest path problem.. |
MLA | Ji, XY."Models and algorithm for stochastic shortest path problem".(2010). |
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