A method for stochastic multiple criteria decision making based on dominance degrees

Liu, Yang; Fan, Zhi‐Ping; Zhang, Yao

doi:10.1016/j.ins.2011.05.013

Cited by 46 publications

(27 citation statements)

References 35 publications

(98 reference statements)

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“…It can be seen from Table 4 that the results obtained by the proposed SDD method and those by the existing methods are slightly different. However, the proposed method and Liu and Fan's method [18] could produce more accurate results than the others. When comparing with the existing methods, the new method takes the risk preference styles and group utility distribution of stakeholders into account.…”

Section: Comparative Analysis and Discussionmentioning

confidence: 82%

“…The results obtained by different SDD, Zaras and Martel's method [29], Nowak's method [12], and Liu and Fan's method [18] are shown in Table 4. It can be seen from Table 4 that the results obtained by the proposed SDD method and those by the existing methods are slightly different.…”

Section: Comparative Analysis and Discussionmentioning

confidence: 99%

“…Following Martel and Zaras [29], Nowak [12], and Liu et al [18], we consider the same problem of selecting the most desirable one from ten computer development projects (A1, A2, ..., A10). The decision-making committee assesses the projects based on four attributes which follow: (1) personal resources effort (C1); (2) The evaluation group is constituted by seven experts.…”

Section: Illustrative Applicationsmentioning

confidence: 99%

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A New Stochastic Dominance Degree Based on Almost Stochastic Dominance and Its Application in Decision Making

Sun

et al. 2017

Entropy

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Abstract:Traditional stochastic dominance rules are so strict and qualitative conditions that generally a stochastic dominance relation between two alternatives does not exist. To solve the problem, we firstly supplement the definitions of almost stochastic dominance (ASD). Then, we propose a new definition of stochastic dominance degree (SDD) that is based on the idea of ASD. The new definition takes both the objective mean and stakeholders' subjective preference into account, and can measure both standard and almost stochastic dominance degree. The new definition contains four kinds of SDD corresponding to different stakeholders (rational investors, risk averters, risk seekers, and prospect investors). The operator in the definition can also be changed to fit in with different circumstances. On the basis of the new SDD definition, we present a method to solve stochastic multiple criteria decision-making problem. The numerical experiment shows that the new method could produce a more accurate result according to the utility situations of stakeholders. Moreover, even when it is difficult to elicit the group utility distribution of stakeholders, or when the group utility distribution is ambiguous, the method can still rank alternatives.

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Section: Comparative Analysis and Discussionmentioning

confidence: 82%

Section: Comparative Analysis and Discussionmentioning

confidence: 99%

Section: Illustrative Applicationsmentioning

confidence: 99%

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A New Stochastic Dominance Degree Based on Almost Stochastic Dominance and Its Application in Decision Making

Sun

et al. 2017

Entropy

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“…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%

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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“…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%

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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A method for stochastic multiple criteria decision making based on dominance degrees

Cited by 46 publications

References 35 publications

A New Stochastic Dominance Degree Based on Almost Stochastic Dominance and Its Application in Decision Making

A New Stochastic Dominance Degree Based on Almost Stochastic Dominance and Its Application in Decision Making

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

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