Stochastic programming: Difference between revisions

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The most widely applied and studied stochastic programming models are two-stage [[linear program|linear programs]]. Here the decision maker takes some action in the first stage, after which a random event occurs affecting the outcome of the first-stage decision. A recourse decision can then be made in the second stage that compensates for any bad effects that might have been experienced as a result of the first-stage decision. The optimal policy from such a model is a single first-stage policy and a collection of recourse decisions (a decision rule) defining which second-stage action should be taken in response to each random outcome.

==Biological Applications==

For further information, see the [http://stoprog.org Stochastic Programming Community Home Page], which is also the source of this article.

Stochastic dynamic programming is frequently used to model [[optimalanimal behaviour]] in such fields such as [[behavioural ecology]]<ref>Mangel, M. & Clark, C. W. 1988. ''Dynamic modeling in behavioral ecology.'' Princeton University Press ISBN 0-691-08506-4</ref><ref>Houston, A. I & McNamara, J. M. 1999. ''Models of adaptive behaviour: an approach based on state''. Cambridge University Press ISBN 0-521-65539-0</ref>. Empirical tests of models of [[Optimal foraging theory|optimal foraging]], [[Biological life cycle|life-history]] transitions such as [[Fledge|fledging in birds]] and egg laying in [[parasitoid]] wasps have shown the value of this modelling technique in explaining the evolution of behavioural decision making. These models are typically many, rather than two-staged.

==References==

Stochastic dynamic programming is frequently used to model [[optimal behaviour]] in fields such as [[behavioural ecology]]<ref>Mangel, M. & Clark, C. W. 1988. ''Dynamic modeling in behavioral ecology'' Princeton University Press ISBN 0-691-08506-4</ref><ref>Houston, A. I & McNamara, J. M. 1999. Models of adaptive behaviour. Cambridge University Press ISBN 0-521-65539-0</ref>. Empirical tests of models of optimal foraging, life-history transitions such as fledging in birds and egg laying in parasitoid wasps have shown the value of this modelling technique in explaining the evolution of behavioural decision making.

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==External Links==

For further information, see the [http://stoprog.org Stochastic Programming Community Home Page], which is also the source of this article.

[[Category:Operations research]]