Wyniki wyszukiwania - Biblioteka Nauki

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Propozycja hybrydy reguł Hurwicza i Bayesa w podejmowaniu decyzji w warunkach niepewności

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Gaspars-Wieloch H.

Studia Ekonomiczne

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2014

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tom 178

74-92

EN

The Hurwicz rule and the Bayes rule are classical approaches applied in the decision making under uncertainty. This situation occurs when the decision maker may choose one of several alternatives and he or she is only able to assign to each of them an interval of potential payoffs or a set of possible profits. In both cases the answer obtained depends on the state of nature (scenario) which will happen, but in the first case the set of scenarios is infinite and in the second one - it is finite. The Hurwicz measure, with the aid of the coefficient of pessimism and the coefficient of optimism, enables to find the optimal pure strategy when the decision selected is performed only once. Meanwhile the Bayes criterion is designed to indicate the optimal pure or mixed strategy when the variant chosen is performed once or many times. In the first part of the article the author analyzes the Hurwicz rule and illustrates cases when the use of this criterion leads to quite unexpected results which seem to be contradictory with the logic and do not reflect the decision maker's preferences. In the second part a proposal of an approach for optimal pure strategy searching (by means of formulas considering both the coefficients of pessimism and optimism, as well as the whole set of payoffs) is presented. This procedure (H+B rule) combines elements of the Hurwicz criterion and the Bayes criterion, but is deprived of disadvantages typical of the Hurwicz rule. The rule suggested takes into consideration both extreme payoffs and intermediate payoffs, which enables to receive rational recommendations for a larger spectrum of decision problems. The H+B rule may be applied in the decision making process under uncertainty when the number of potential scenarios and the set of possible payoffs are finite, however a slight modification of the equations proposed enables to use this procedure in problems with continuous payoffs.

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MODIFICATIONS OF THE MAXIMIN JOY CRITERION FOR DECISION MAKING UNDER UNCERTAINTY

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Gaspars-Wieloch H.

Metody Ilościowe w Badaniach Ekonomicznych

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2014

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tom 15

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nr 2

84-93

EN

Decision making under uncertainty (DMU) occurs when the decision maker (DM) has to choose an appropriate alternative on the basis of a set of decisions and a set of scenarios (with an unknown probability distribution). The author suggests two modifications of the maximin joy criterion (MJC) - one of the classical decision rules used in DMU by pessimists searching for an optimal pure strategy. The goal of the alterations for MJC is to accentuate more effectively the position of particular outcomes in comparison with other outcomes connected with a given scenario.

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O regule decyzyjnej wspierającej wielokryterialne poszukiwanie optymalnej strategii czystej w warunkach niepewności

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Gaspars-Wieloch H.

Studia Ekonomiczne

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2015

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tom 248

42-61

PL

W pracy opisano propozycję nowego podejścia, które można wykorzystać w wielokryterialnym podejmowaniu decyzji w przypadku poszukiwania optymalnej strategii czystej w warunkach niepewności (decydent nie zna bądź nie zamierza skorzystać z informacji o prawdopodobieństwie wystąpienia poszczególnych stanów natury). Prezentowana reguła decyzyjna poprzedzona jest etapem prognostycznym, w ramach którego brane jest pod uwagę nastawienie decydenta do ryzyka (rozumianego jako możliwość uzyskania niekorzystnej wypłaty) mierzone współczynnikiem optymizmu. Etap ten służy do wyłonienia najbardziej „prawdopodobnego” (tj. odzwierciedlającego naturę decydenta) scenariusza bądź zbioru najbardziej „prawdopodobnych” scenariuszy i ma na celu zawężenie pierwotnej macierzy wypłat, na podstawie której wybierana jest najlepsza decyzja. Procedura odwołuje się do planowania scenariuszowego i do metody SF+AS (ang. Scenario Forecasting + Alternative Selection Method) przedstawionej w innym artykule i znajdującej zastosowanie w jednokryterialnych problemach decyzyjnych.

EN

The author describes a new approach which may be used in uncertain multicriteria decision making with scenario planning to searching an optimal pure strategy. The decision maker does not know the likelihood of particular scenarios. The decision rule is supported by a forecasting stage within which scenarios reflecting the decision maker’s attitude towards risk (understood as a possibility that some bad circumstances might happen) are selected. The nature of the decision maker is measured by the coefficient of optimism. Hence, the final strategy is chosen on the basis of a reduced aggregated payoff matrix. The procedure refers to SAW (Simple Additive Weighting Method) and to SF+AS method (Scenario Forecasting + Alternative Selection Method), presented in an other paper and devoted to one-criterion decision problems.

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A decision rule for uncertain multicriteria mixed decision making based on the coefficient of optimism

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Gaspars-Wieloch H.

Multiple Criteria Decision Making

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2015

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tom 10

32-47

EN

This paper is devoted to multicriteria decision making under uncertainty with scenario planning. This topic has been explored by many researchers since almost all real-world decision problems contain multiple conflicting criteria and a deterministic criteria evaluation is often impossible. We propose a procedure for uncertain multi-objective optimization which may be applied when a mixed strategy is sought after. A mixed strategy, as opposed to a pure strategy, allows the decision maker to select and perform a weighted combination of several accessible alternatives. The new approach takes into account the decision maker’s preference structure and attitude towards risk. This attitude is measured by the coefficient of optimism on the basis of which a set of the most probable events is suggested and an optimization problem is formulated and solved.