On a Decision Rule for Mixed Strategy Searching Under Uncertainty on the basis of the Coefficient of Optimism

Gaspars-Wieloch, Helena

doi:10.1016/j.sbspro.2013.12.938

Cited by 14 publications

(12 citation statements)

References 17 publications

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“…These parameters belong to interval [0,1] and satisfy the condition α+β=1, where α (β) tends to 0 (1) for extreme optimists (risk-prone behavior) and is close to 1 (0) for radical pessimists (risk-averse behavior). The coefficients of pessimism and optimism have been already used in decision rules suggested for instance by [Gaspars-Wieloch, 2014b;2015a;Hurwicz, 1952;Perez et al, 2015].…”

Section: Procedures For Mdmu+sp Pure Strategies and Independent Criteriamentioning

confidence: 99%

A Decision Rule for Uncertain Multi-Criteria Pure Decision Making and Independent Criteria

Gaspars-Wieloch

2017

Optimum

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SummaryThe paper is concerned with multi-criteria 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 evaluation of criteria is often impossible. We propose a procedure for uncertain multi-objective optimization which can be applied when seeking a pure strategy. A pure strategy, as opposed to a mixed strategy, allows the decision-maker to select and perform only one accessible alternative. The new approach takes into account the decision-maker's preference structure (importance of particular goals) and nature (pessimistic, moderate or optimistic attitude towards a given problem). It is designed for one-shot decisions made under uncertainty with unknown probabilities (frequencies), see decision-making under complete uncertainty or decision-making under strategic uncertainty. The novel approach can be used in the case of totally independent payoff matrices for particular targets.

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Section: Procedures For Mdmu+sp Pure Strategies and Independent Criteriamentioning

confidence: 99%

A Decision Rule for Uncertain Multi-Criteria Pure Decision Making and Independent Criteria

Gaspars-Wieloch

2017

Optimum

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“…α (β) tends to 0 (1) for extreme optimists (risk-prone behavior) and is close to 1 (0) for radical pessimists (risk-averse behavior). Coefficients of pessimism and optimism have been already used in decision rules described, for example, in [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [35], [54]. As mentioned before, the decision rule presented in this paper enables the DM to find an optimal mixed strategy, but it is worth emphasizing that the existing onecriterion and multi-criteria procedures for mixed strategies are related more to game theory, i.e.…”

Section: Uncertain Multi-criteria Decision Making and 1-stage Modelsmentioning

confidence: 99%

“…Conclusions are gathered in the last Section. The paper is a continuation of several articles, where uncertain one-criterion procedures [16], [18], [22] and multi-criteria decision rules for 2-stage models [20], [24], [25] were investigated.…”

Section: Introductionmentioning

confidence: 99%

A decision rule based on goal programming and one-stage models for uncertain multi-criteria mixed decision making and games against nature

Gaspars-Wieloch

2017

CRORR

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Abstract. This paper is concerned with games against nature and multi-criteria decision making under uncertainty along with scenario planning. We focus on decision problems where a deterministic evaluation of criteria is not possible. The procedure we propose is based on weighted goal programming and may be applied when seeking a mixed strategy. A mixed strategy allows the decision maker to select and perform a weighted combination of several accessible alternatives. The new method takes into consideration the decision maker's preference structure (importance of particular goals) and nature (pessimistic, moderate or optimistic attitude towards a given problem). It is designed for one-shot decisions made under uncertainty with unknown probabilities (frequencies), i.e for decision making under complete uncertainty or decision making under strategic uncertainty. The procedure refers to one-stage models, i.e. models considering combinations of scenarios and criteria (scenario-criterion pairs) as distinct meta-attributes, which means that the novel approach can be used in the case of totally independent payoff matrices for particular targets. The algorithm does not require any information about frequencies, which is especially desirable for new decision problems. It can be successfully applied by passive decision makers, as only criteria weights and the coefficient of optimism have to be declared.

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“…The literature offers numerous decision rules for DMPI [Guo 2013;Kmietowicz, Pearman 1984;Kofler, Zweifel 1993;Michalska, Pośpiech 2010;, Michalska 2012Weber 1987] and for DMCU [Gaspars 2007;GasparsWieloch 2013;2014a;2014b;2014c;2014d;2014e;2015a;2015b;2015c;2015d;2015e;2016;Hayashi 2008;Hurwicz 1952;Ioan, Ioan 2011;Piasecki 1990;Savage 1961;Wald 1950], but here we only investigate the use of the Ω ratio in these two decision cases.…”

Section: Decision Making With Partial Information and Under Uncertainmentioning

confidence: 99%

On two applications of the Omega ratio: max?min and Omega(H+B) / O dwóch zastosowaniach wskaźnika Omega: max?min i Omega(H+B)

Gaspars-Wieloch¹,

Michalska²

2016

Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu

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On a Decision Rule for Mixed Strategy Searching Under Uncertainty on the basis of the Coefficient of Optimism

Cited by 14 publications

References 17 publications

A Decision Rule for Uncertain Multi-Criteria Pure Decision Making and Independent Criteria

A Decision Rule for Uncertain Multi-Criteria Pure Decision Making and Independent Criteria

A decision rule based on goal programming and one-stage models for uncertain multi-criteria mixed decision making and games against nature

On two applications of the Omega ratio: max?min and Omega(H+B) / O dwóch zastosowaniach wskaźnika Omega: max?min i Omega(H+B)

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