On Decision Making under Interval Uncertainty: A New Justification of Hurwicz Optimism-Pessimism Approach and its Use in Group Decision Making

Huynh, Van–Nam; Nakamori, Yoshiteru; Hu, Chenyi; Kreinovich, Vladik

doi:10.1109/ismvl.2009.65

Cited by 12 publications

(8 citation statements)

References 6 publications

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“…Notice that the decision making under uncertainty may not necessarily signify the occurrence of a finite number of scenarios with a set of m profits for each decision. In the other concept of DMUU it is assumed that the exact profit connected with the alternative I j is not known, but belongs to an interval [w j , m j ] and then we deal with the decision making under interval uncertainty (Huynh et al 2007). In such a case each value from this interval is probable.…”

Section: Decision Making Under Uncertainty: Characteristics and Assummentioning

confidence: 99%

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Modifications of the Hurwicz’s decision rule

Gaspars-Wieloch

2013

Cent Eur J Oper Res

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The Hurwicz's criterion is one of the classical decision rules applied in decision making under uncertainty as a tool enabling to find an optimal pure strategy both for interval and scenarios uncertainty. The interval uncertainty occurs when the decision maker knows the range of payoffs for each alternative and all values belonging to this interval are theoretically probable (the distribution of payoffs is continuous). The scenarios uncertainty takes place when the result of a decision depends on the state of nature that will finally occur and the number of possible states of nature is known and limited (the distribution of payoffs is discrete). In some specific cases the use of the Hurwicz's criterion in the scenarios uncertainty may lead to quite illogical and unexpected results. Therefore, the author presents two new procedures combining the Hurwicz's pessimism-optimism index with the Laplace's approach and using an additional parameter allowing to set an appropriate width for the ranges of relatively good and bad payoffs related to a given decision. The author demonstrates both methods on the basis of an example concerning the choice of an investment project. The methods described may be used in each decision making process within which each alternative (decision, strategy) is characterized by only one criterion (or one synthetic measure).

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Section: Decision Making Under Uncertainty: Characteristics and Assummentioning

confidence: 99%

“…Notice that one may find in the literature examples where the parameter α describes the user's degree of optimism (Groenewald and Pretorius 2011;Huynh et al 2007;Pazek and Rozman 2009) and not the pessimism index.…”

Section: Hurwiczmentioning

confidence: 99%

Modifications of the Hurwicz’s decision rule

Gaspars-Wieloch

2013

Cent Eur J Oper Res

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“…A combination of scale-and shift-invariance explains Hurwicz's empirical formula for decision making under interval uncertainty [5].…”

Section: Other Economics-related Examples: In Briefmentioning

confidence: 99%

Symmetries: A General Approach to Integrated Uncertainty Management

Kreinovich

Nguyen

Sriboonchitta

2010

Advances in Intelligent and Soft Computing

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We propose to use symmetries as a general approach to maintaining different types of uncertainty, and we show how the symmetry approach can help, especially in economics-related applications. Why SymmetriesFormulation of the problem. Our knowledge is rarely complete, we rarely have absolutely certainty. Uncertainty is present in different areas of knowledge. As a result, in many different areas of knowledge, different techniques and approaches have been developed to describe and process uncertainty. For example, in logical-type descriptions of knowledge typical for expert systems and Artificial Intelligence, formalisms like probabilistic logic and fuzzy logic have been developed to process uncertainty. In engineering-oriented probability-type descriptions, probability-related approaches have been developed such as the Dempster-Shafer approach, imprecise probabilities approach, etc.To solve complex real-life problems, we must takes into account knowledge form different areas. Since these different pieces of knowledge come with uncertainty, we must therefore jointly manage different types of uncertainty. We therefore need a general approach that would take care of different types of uncertainty.

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“…Sometimes the distribution of payoffs connected with particular alternatives is not discrete and then the profits for each decision D j belong to an interval [w j , m j ] (Branzei et al 2011;Gaspars-Wieloch 2013a, 2014bHuynh et al 2009). In this paper we will focus on the scenario approach for DMUU which has a lower degree of uncertainty than the interval approach because only several outcomes from this range may occur.…”

Section: Introductionmentioning

confidence: 99%

On a decision rule supported by a forecasting stage based on the decision maker’s coefficient of optimism

Gaspars-Wieloch

2014

Cent Eur J Oper Res

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The paper contains a description of a new approach (called the SF + AS method, i.e. the scenario forecasting + alternative selection method) that can be used in decision making under uncertainty when pure optimal strategies are sought-after. This procedure takes into consideration the level of decision maker's coefficient of optimism (or coefficient of pessimism) and consists of two stages: the true scenario forecasting (on the basis of the decision maker's preferences) and the appropriate alternative selection by taking into account the payoffs of the appointed true scenario or the most probable scenarios. In contradiction to existing decision rules, this procedure assumes that the decision making process should involve only a part of the payoff matrix because only one state of nature will occur in the end. The second essential difference between the SF + AS method and other decision rules is that in the first one there is an attempt to appoint globally the best and the worst scenario (regardless the alternative considered). Meanwhile, other procedures determine the status of a given event depending on the decision.

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On Decision Making under Interval Uncertainty: A New Justification of Hurwicz Optimism-Pessimism Approach and its Use in Group Decision Making

Cited by 12 publications

References 6 publications

Modifications of the Hurwicz’s decision rule

Modifications of the Hurwicz’s decision rule

Symmetries: A General Approach to Integrated Uncertainty Management

On a decision rule supported by a forecasting stage based on the decision maker’s coefficient of optimism

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