Abstract
This paper deals with an extension of the minimum-risk criterion considered by B. Bereanu [5, 6, 7] and A. Charnes and W. W. Cooper [11] in the linear case to the nonlinear mathematical programming case. In what follows the minimum-risk criterion is applied to some special classes of nonlinear problems as are, for instance, linear Tchebysheff problems, bottlenech transportation problems, max-min (linear or linear fractional) problems with linked constraints, max-min bilinear programming problems. It is shown that, under certain hypotheses, these stochastic problems are equivalent to deterministic fractional problems. The last section examines the vectorial minimum-risk problem. The ideas discussed in this paper string together the developments given by the authors in [33–38, 43–45].
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Stancu-Minasian, I.M., Tigan, S. (1990). On Some Fractional Programming Models Occurring in Minimum-Risk Problems. In: Cambini, A., Castagnoli, E., Martein, L., Mazzoleni, P., Schaible, S. (eds) Generalized Convexity and Fractional Programming with Economic Applications. Lecture Notes in Economics and Mathematical Systems, vol 345. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-46709-7_22
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