Multistage Stochastic Decision and Economic Processes
نویسندگان
چکیده
منابع مشابه
Decision dependent stochastic processes
0377-2217/$ see front matter 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ejor.2013.11.016 ⇑ Corresponding author. Tel.: +1 512 471 3322. E-mail addresses: [email protected] (T. Kirschenmann), elmira@mail. utexas.edu (E. Popova), [email protected] (P. Damien), hansont@ stat.sc.edu (T. Hanson). Thomas Kirschenmann , Elmira Popova , Paul Damien c,⇑, Tim H...
متن کاملBound-based decision rules in multistage stochastic programming
Forschungsplattform Alexandria https://www.alexandria.unisg.ch | 03.01.2016 We study bounding approximations for a multistage stochastic program with expected value constraints. Two simpler approximate stochastic programs, which provide upper and lower bounds on the original problem, are obtained by replacing the original stochastic data process by finitely supported approximate processes. We m...
متن کاملStep decision rules for multistage stochastic programming: A heuristic approach
Stochastic programming with step decision rules, SPSDR, is an attempt to overcome the curse of computational complexity of multistage stochastic programming problems. SPSDR combines several techniques. The first idea is to work with independent experts. Each expert is confronted with a sample of scenarios drawn at random from the original stochastic process. The second idea is to have each expe...
متن کاملModeling multistage decision processes with Reflexive Game Theory
This paper introduces application of Reflexive Game Theory to the matter of multistage decision making processes. The idea behind is that each decision making session has certain parameters like “when the session is taking place”, “who are the group members to make decision”, “how group members influence on each other”, etc. This study illustrates the consecutive or sequential decision making p...
متن کاملMultistage Markov Decision Processes with Minimum Criteria of Random Rewards
We consider multistage decision processes where criterion function is an expectation of minimum function. We formulate them as Markov decision processes with imbedded parameters. The policy depends upon a history including past imbedded parameters, and the rewards at each stage are random and depend upon current state, action and a next state. We then give an optimality equation by using operat...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Acta Oeconomica Pragensia
سال: 2005
ISSN: 0572-3043,1804-2112
DOI: 10.18267/j.aop.143