By P.M. Pardalos
The fast adjustments that experience taken position globally at the fiscal, social and enterprise fronts characterised the twentieth century. The significance of those alterations has shaped an exceptionally advanced and unpredictable decision-making framework, that's tough to version via conventional techniques. the most goal of this publication is to offer the latest advances within the improvement of cutting edge thoughts for dealing with the uncertainty that prevails within the international monetary and administration environments. those suggestions originate typically from fuzzy units conception. even if, the booklet additionally explores the mixing of fuzzy units with different determination help and modelling disciplines, comparable to multicriteria determination relief, neural networks, genetic algorithms, desktop studying, chaos thought, etc. The presentation of the advances in those fields and their actual global purposes provides a brand new standpoint to the wide fields of administration technological know-how and economics.
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Extra resources for Fuzzy Sets in Management, Economy & Marketing
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Linear shapes that give a linear program, that in several authors' opinions [14, 17], are valid for most practical applications. Nevertheless other shapes may be used. We deal with the unfeasibility of the problem, due to initial DM preferences, relaxing some veto threshold, in an interactive way. Our problem solution maximizes a global measure of the degrees of achievement of goals. We have used the weighted mean, although more complex aggregation functions may also be considered. The solution obtained through our approach is more balanced than the classic one with regard to the achievement of the aspiration levels of objective functions because, in general, it is preferable to satisfy fewer goals in total, with only minimum deviations in those which are not satisfied.
25- P f i + 0 . 9 , Pg. , M10 , PlO , nU , Pll , "12 , Pl2. 4 200 4187 400 Pl3 , w 14 , Pl4 , W 1S ,. t. 5; n16<164 With all variables non-negative. This problem is unfeasible. 33 yn = 218400; 12) n12 - Pn + yn - 10000; 13) nn-pn + yn = 20000; 21) n3 <= 10920; 37) pn <=4187; 39) p 13 <=2663 (10) According to this result, to make the problem feasible the decision-maker should increase the left tolerance margin of Consulting Nurses and the right tolerance margin of desirable activity level of Following Appointments (y12) and Ambulatory Emergency (y^).
See Zadeh [50], Bonissone and Decker [10] and Delgado, Verdegay and Vila [14], among others. Generally, fuzzy sets and fuzzy preferences are evaluated on L = [0,1]. Nevertheless, some authors have used lattices and other kind of sets. See Goguen [20] and Barrett, Pattanaik and Salles [3], among others. 40 This scheme is similar to others used in the literature , but in [0,1] instead of L. We note that the condition r.. = \h 0 r .. = / ^ appearing in Definition 2 is related to the reciprocity axiom sometimes required in the modelization of preferences by means of fuzzy binary relations10.