Abstract
This paper considers linear programming problems where each coefficient of the objective function is expressed by a random fuzzy variable. New decision making models are proposed based on stochastic and possibilistic programming in order to maximize both of possibility and probability with respect to the objective function value. It is shown that each of the proposed models is transformed into a deterministic equivalent one. Solution algorithms using convex programming techniques and/or the bisection method are provided for obtaining an optimal solution of each model.
| Original language | English |
|---|---|
| Article number | 4811548 |
| Pages (from-to) | 1788-1793 |
| Number of pages | 6 |
| Journal | Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics |
| DOIs | |
| Publication status | Published - 2008 Dec 1 |
| Externally published | Yes |
| Event | 2008 IEEE International Conference on Systems, Man and Cybernetics, SMC 2008 - Singapore, Singapore Duration: 2008 Oct 12 → 2008 Oct 15 |
Keywords
- Linear program
- Random fuzzy programming models
- Random fuzzy variable
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Human-Computer Interaction
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Cite this
Katagiri, H., Hasuike, T., & Ishii, H. (2008). A random fuzzy programming models based on possibilistic programming. Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, 1788-1793. [4811548]. https://doi.org/10.1109/ICSMC.2008.4811548