Decision problems, multistage

Yu, P. L., and Seiford, L. (1981), Multistage Decision Problems with Multicriteria, in Multicriteria Analysis Practical Methods, P. NijKamp and 1. Spronk, Eds, Gower Press, London. 

Dynamic programs and multistage stochastic programs deal with essentially the same types of problems, namely dynamic and stochastic decision problems. The major distinction between dynamic programming and stochastic programming is in the structures that are used to formulate the models. For example, in DP, the so-called state of the process, as weU as the value function, that depends on the state, are two structures that play a central role, but these concepts are usually not used in stochastic programs. Section 4.1 provides an introduction to concepts that are important in dynamic programming. 

A more complete method is the Dynamic programming method for solving problems that can be viewed as multistage decision processes. The objective in analyzing such processes is to determine an optimal policy, one that results in the best total return (Chryssolouris 2006). 

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