MCDM'07 - paper no. 12

 

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Fuzzy multiobjective methods in multistage decision problems

Jaroslav Ramík, Jana Hanclova, Tadeusz Trzaskalik, Sebastian Sitarz

Abstract:

In this paper we propose a new approach for solving dynamic multi-objective decision making problems. The decision variants are generated in a discrete multi-stage model by forward/backward procedure of finding the set of all maximal elements based on Bellman's principle of optimality. As the set of all maximal elements consists of a number of elements - decision variants, our problem is to find among them a compromise element based on decision maker´s preferences with respect to several decision criteria. The evaluation of the weights of the criteria is based on data given by pairwise comparison matrices using triangular fuzzy numbers. Extended arithmetic operations with fuzzy numbers for application of the generalized logarithmic least squares method are defined and six methods for ranking fuzzy numbers to compare fuzzy outcomes are proposed. A numerical example is presented to clarify the methodology.

Keywords:

Multi-criteria decision making, dynamic programming, multistage decision process, pairwise comparisons, fuzzy numbers, analytic hierarchy process (AHP)

Reference index:

Jaroslav Ramík, Jana Hanclova, Tadeusz Trzaskalik, Sebastian Sitarz, (2008), Fuzzy multiobjective methods in multistage decision problems, Multiple Criteria Decision Making (3), pp. 195-214

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Scopus citations in 1 paper(s):
  1. Gaspars-Wieloch, H. (2017). A decision rule based on goal programming and one-stage models for uncertain multi-criteria mixed decision making and games against nature. Croatian Operational Research Review, 8(1), 61-76. doi:10.17535/crorr.2017.0004