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Stochastic Dependent-Chance Programming

  • Baoding Liu
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 102)

Abstract

In practice, there usually exist multiple events in a complex stochastic decision system. Sometimes, the decision-maker wishes to maximize the chance functions of these events (i.e., the probabilities of satisfying the events). In order to model this type of stochastic decision system, Liu [160] provided the third type of stochastic programming, called dependent-chance programming (DCP), in which the underlying philosophy is based on selecting the decision with maximal chance to meet the event.

Keywords

Genetic Algorithm Topological Optimization Stochastic Simulation Priority Level Uncertain Environment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Baoding Liu
    • 1
  1. 1.Uncertain Systems Laboratory, Department of Mathematical SciencesTsinghua UniversityBeijingChina

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