Scenario Planning + MCDA Procedure For Innovation Selection Problem

Michnik, Jerzy

doi:10.2478/fcds-2013-0010

Cited by 14 publications

(17 citation statements)

References 22 publications

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“…There are many classical and extended decision rules designed for multi-criteria decision making under uncertainty, e.g. [1], [2], [7], [8], [11], [13], [20], [24], [25], [28], [29], [34], [36], [40], [41], [42], [45], [48], [49], [50], [51], [56], [57], [58], [61], [62], [63], [65], [66], [71], [74], [75], [76], however the majority of the methods refer to probability calculus. Hence, those contributions are not directly related to the topic investigated in this paper, since here we concentrate on totally new decision problems for which frequencies are not known.…”

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

confidence: 99%

“…Therefore, devising an approach for uncertain multi-objective mixed decision making and games against nature seems vital and desirable [24], [63]. According to [12], [48] MDMU+SP models can be divided into two classes. The first class (A) includes 2-stage models in which evaluations of particular alterna-tives are estimated in respect of scenarios and criteria in two separate stages.…”

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

confidence: 99%

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

confidence: 99%

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

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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“…Some of them state that the likelihood should not be applied to SP [Michnik, 2013]. Others are convinced that there are many advantages of using probabilities in SP [Millett, 2009].…”

Section: How To Combine Criteria With Scenarios In Uncertain Multi-crmentioning

confidence: 99%

“…Many classical and extended decision rules designed for pure or mixed MDMU (multi-criteria decision-making under uncertainty) have been already developed, e.g. [Aghdaie et al, 2013;Ben Amor et al, 2007;Dominiak, 2006;Durbach, 2014;Eiselt, Marianov, 2014;GasparsWieloch, 2014d;2015c;2015d;2017;Ginevičius, Zubrecovas, 2009;Goodwin, Wright, 2001;Hopfe et al, 2013;Janjic et al, 2013;Korhonen, 2001;Lee, 2012;Liu et al, 2011;Lo, Michnik, 2010;Michnik, 2013;Mikhaidov, Tsvetinov, 2004;Montibeller et al, 2006;Ram et al, 2010;Ramik et al, 2008;Ravindran, 2008;Silva, 2016;Stewart, 2005;Suo et al, 2012;Troutt, Pettypool, 1989;Tsaur et al, 2002;Urli, Nadeau, 2004;Wojewnik, Szapiro, 2010;Xu, 2000;Yu, 2002]. Some of them can be applied when the DM intends to perform the selected alternative only once (one-shot decisions).…”

Section: How To Combine Criteria With Scenarios In Uncertain Multi-crmentioning

confidence: 99%

“…According to [Durbarch, Stewart, 2012;Michnik, 2013] MDMU+SP models can be divided into two classes (the description below has been prepared on the basis of [Gaspars-Wieloch, 2014d;2015c;2015d;2017]). The first one (A) includes 2-stage models in which evaluations of particular alternatives are estimated in respect of scenarios and criteria in two separate stages.…”

Section: How To Combine Criteria With Scenarios In Uncertain Multi-crmentioning

confidence: 99%

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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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AHP based on scenarios and the optimism coefficient for new and risky projects: case of independent criteria

Gaspars-Wieloch

2024

Ann Oper Res

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AHP is a well-known multi-criteria procedure which has been investigated and developed by many researchers and practitioners. Some AHP modifications are designed for decision making under uncertainty. The goal of this paper is to present a new AHP approach which can be useful in the case of uncertain one-shot decisions and independent criteria. The method proposed in the article is based on scenario planning, features characteristic for the Hurwicz rule (i.e. the use of the optimism coefficient) and on a scenario set reduction. The novel procedure gives the possibility to generate a relatively small number of pairwise comparison matrices thanks to the reduction of the initial sets of scenarios. The modified version of AHP may be helpful when the decision maker’s knowledge about probabilities of the occurrence of particular scenarios is partial. Such a situation occurs in the case of innovative, innovation and risky projects for which historical data are not known. The idea of the suggested scenario-based AHP is to adjust the final choice not only to the decision makers’ preferences (concerning criteria for example), but also to their nature, attitude towards risk, predictions, expectations and fears.

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Scenario Planning + MCDA Procedure For Innovation Selection Problem

Cited by 14 publications

References 22 publications

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

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

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

AHP based on scenarios and the optimism coefficient for new and risky projects: case of independent criteria

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