MCDM'08 - paper no. 12

 

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Dynamic stochastic problems of profit maximization with partially ordered criteria space

Tadeusz Trzaskalik, Sebastian Sitarz

Abstract:

Stochastic dynamic programming (DP) is a strong mathematical tool allowing modeling and solving many multiperiod decision processes. Multiple objective and dynamics characterize many sequential decision problems. In the paper we consider returns in partially ordered criteria set as a way of generalization of single criterion DP models to multiobjective case.
In the present paper, on the basis of theoretical findings, described in our previous papers we consider exemplary stochastic DP profit maximization processes. Because of the lack of space we omit the general, formal description of such a process and concentrate on explanation, how the theory of DP models in partially ordered criteria space works. Both in level-volume and velocity-volume process we will consider formulated problems step by step, first as single criterion problems and next as bi-criteria ones. Conclusions are presented in the last section.

Keywords:

Stochastic dynamic programming, multiobjective dynamic optimization, profit maximization, partially ordered criteria space

Reference index:

Tadeusz Trzaskalik, Sebastian Sitarz, (2009), Dynamic stochastic problems of profit maximization with partially ordered criteria space, Multiple Criteria Decision Making (4), pp. 215-226

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Scopus citations in 1 paper(s):
  1. Nowak, M., & Trzaskalik, T. (2012, 12). Interactive procedure for a multiobjective stochastic discrete dynamic problem. Journal of Global Optimization, 57, 315-330. doi:10.1007/s10898-012-0019-9