Preference and veto thresholds in multicriteria analysis based on stochastic dominance

Nowak, Maciej

doi:10.1016/j.ejor.2003.06.008

Cited by 73 publications

(57 citation statements)

References 20 publications

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“…for all increasing convex functions u : R m → R, which is thought as very conservative in practice (see Zaras and Martel (1994) and Nowak (2004)). In fact, the homeland security case study model in Sections 4-6 becomes infeasible if the notion of positive linear second order dominance is used.…”

Section: A Robust Optimization Model With Stochastic Dominance Constrmentioning

confidence: 99%

Risk-adjusted budget allocation models with application in homeland security

Homem-de-Mello

Mehrotra

2011

IIE Transactions

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This paper presents and studies models for multi-criterion budget allocation problems under uncertainty. The proposed models incorporate uncertainties in decision maker's weights using a robust weighted sum approach. The risk averseness of the decision maker in satisfying random risk related constraints is ensured by using stochastic dominance. A sample average approximation approach together with a cutting surface method is used to solve this model. An analysis for the computation of statistical lower and upper bounds is also given. We use the proposed models to study the budget allocation to ten urban areas in the United States under the Urban Areas Security Initiative (UASI). Here the decision maker considers property losses, fatalities, air departures, and average daily bridge traffic as separate criteria. The properties of the proposed modeling and solution methodology are discussed using a RAND Corporation proposed allocation policy and the current government budget allocation as two benchmarks. The budget results are discussed under several parameter scenarios.

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Section: A Robust Optimization Model With Stochastic Dominance Constrmentioning

confidence: 99%

Risk-adjusted budget allocation models with application in homeland security

Homem-de-Mello

Mehrotra

2011

IIE Transactions

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“…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%

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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“…Nowadays, researchers are proposed approaches using stochastic dominance (SD) rules [19][20][21][22][23][24][25][26][27][28]. Some of these methods are to rank alternatives by using the determined SD relations based on rough set theory [26][27].…”

Section: Introductionmentioning

confidence: 99%

Attribute Reduction in Stochastic Information Systems Based on α-Dominance

Aydoğan

Özmen

2017

Bilişim Teknolojileri Dergisi

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Abstract-Rough set has been commonly taken part in literature to examine inadequate and incomplete information systems. The efficiency of rough set with stochastic data observed for developing convenience and scalability. In this study, we use a ranking approach for attribute reduction in stochastic information systems and generalized this via presenting a dominance relation. We obtained the rough set approach of attribute reduction in stochastic information systems by establishing the dominance degrees. Furthermore, attribute reduction methods are studied by considering discernibility matrix and this approach is applied to explanatory examples to demonstrate its validity. Also this research proposes many research fields and new application areas show a tendency to concerning rough set approach to stochastic information systems.

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Preference and veto thresholds in multicriteria analysis based on stochastic dominance

Cited by 73 publications

References 20 publications

Risk-adjusted budget allocation models with application in homeland security

Risk-adjusted budget allocation models with application in homeland security

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

Attribute Reduction in Stochastic Information Systems Based on α-Dominance

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