Geodesic
On solution method for possibilistic optimization problem of one class with parameters characterized by quasiconcave upper semicontinuous strictly unimodal distribution functions
Nečetkie sistemy i mâgkie vyčisleniâ, Tome 11 (2016) no. 1, pp. 19-32

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The problem of possibilistic level optimization with parameters characterized by quasiconcave upper semicontinuous strictly unimodal distribution functions is studied. The equivalent crisp analogue is constructed for the problem. We use the weakest and the strongest triangular norms in order to aggregate fuzzy information. Results obtained in the article generalize the case when parameters of the task are characterized by parameterized fuzzy numbers of $(L,R)$-type.
Keywords: possibilistic programming, level optimization, triangular norm, weakest t-norm Tw, indirect solution method, equivalent crisp analogue. 
@article{FSSC_2016_11_1_a1,
     author = {I. S. Soldatenko},
     title = {On solution method for possibilistic optimization problem of one class with parameters characterized by quasiconcave upper semicontinuous strictly unimodal distribution functions},
     journal = {Ne\v{c}etkie sistemy i m\^agkie vy\v{c}isleni\^a},
     pages = {19--32},
     publisher = {mathdoc},
     volume = {11},
     number = {1},
     year = {2016},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/FSSC_2016_11_1_a1/}
}
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I. S. Soldatenko. On solution method for possibilistic optimization problem of one class with parameters characterized by quasiconcave upper semicontinuous strictly unimodal distribution functions. Nečetkie sistemy i mâgkie vyčisleniâ, Tome 11 (2016) no. 1, pp. 19-32. http://geodesic.mathdoc.fr/item/FSSC_2016_11_1_a1/