Aggregation of utility-based individual preferences for group decision-making

Huang, Yeu‐Shiang; Chang, Wei Hung; Li, Wei Hao; Lin, Zu Liang

doi:10.1016/j.ejor.2013.02.043

Cited by 92 publications

(50 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Some earlier MAUT methods of group decision are reviewed by Bose et al (1997), and used by number of works, such as the simple additive theory to aggregate the individuals' utility functions proposed on (Arora and Allenby 1999); the simple additive weighting (SAW) (Kirkwood and Corner 1993); the MAUT group decision model in (Huang et al 2013), which considers both preferential differences and preferential priorities to the model construction; and the use of weighted algebraic means, which is applied in the WINGDSS software (Csáki et al 1995). The group utility function computed in WINGDSS is appropriate in the respect of satisfying the axioms given in Keeney (1976).…”

Section: Related Work and Research Gapmentioning

confidence: 99%

“…We use the additive utility function, which have been used in many early works (e.g., Dyer and Sarin 1979;Keeney 1976), as well as some other recent works (e.g., Alodhaibi et al 2010;Huang et al 2013). We estimate the group utility of a recommendation alternative a k as follows: for each ith dimension, the individual weights of importance of this dimension are aggregated into the group weights w i by calculating the algebraic mean of the individual weights as:…”

Section: Average Strategymentioning

confidence: 99%

See 1 more Smart Citation

A group package recommender based on learning group preferences, multi-criteria decision analysis, and voting

Mengash

Brodsky

2015

EURO Journal on Decision Processes

View full text Add to dashboard Cite

Section: Related Work and Research Gapmentioning

confidence: 99%

Section: Average Strategymentioning

confidence: 99%

A group package recommender based on learning group preferences, multi-criteria decision analysis, and voting

Mengash

Brodsky

2015

EURO Journal on Decision Processes

View full text Add to dashboard Cite

“…In an ordinal ranking and in the presence of strategic voting, the individuals' preferences can also be aggregated to an overall ranking as in Hurley et al [154]. Quite often the individuals' preferential differences among different alternatives and priorities are also considered/weighted to obtain the group utility values, Huang et al [152].…”

Section: Group Decision Makingmentioning

confidence: 99%

“…Quite often the preferential differences among different alternatives and priorities are also considered/weighted to obtain the group utility values, as in Huang [152]. AHP is used to support multiple stakeholders' decision making, Alvarez et al [135]; the geometric mean calculated by AHP is also used in group decision making Lai et al [134] and Sohn et al [141]; while fuzzy AHP techniques are employed in the geometric means computation by Carnero [153].…”

Section: Group Decision Makingmentioning

confidence: 99%

Development and application of a value driven design assessment framework to an unmanned air system design

Papageorgiou

2018

2018 Advances in Science and Engineering Technology International Conferences (ASET)

View full text Add to dashboard Cite

The work presented in this thesis concerns the development of a value driven engineering design assessment framework and its application to the conceptual design of an Unmanned Air System (UAS) to be utilised in a defence application. This research demonstrates the implementation of the value driven design philosophy in this framework, identifying value enhancing designs, with value not converted to monetary worth and as perceived by all stakeholders involved. A multi-criteria and multi-stakeholder decision making analysis is adopted to address their preferences as well as to study their interacting strategic choices. The ultimate objective of this framework is to convert engineering design to a decision making analysis with multiple conflicting objectives of multiple stakeholders considered.This framework is capable of providing a product definition and estimation of all performance and cost related attributes for the conceptual phase. However, instead of pertaining to a single aircraft concept, a broad range of combinations of UAS configurations and geometries is generated by systematically searching alternative concepts and design configurations through a novel parameterization of the aircraft geometric topologies.Value, related to the designed system's capabilities or performance and lifecycle cost, is used to compare different alternatives in the decision making of engineering design through the appropriate value model. Following a valuefocused approach, a novel multi-attribute value model is introduced for objectively capturing the stakeholder's preferences and expectations. Furthermore, a more sophisticated multi-attribute utility model, based on standard Multi-attribute Utility Theory, is employed in the evaluation.Game Theory as an optimization tool is used to develop a novel hybrid cooperative/non-cooperative non-zero sum, complete information game among all involved stakeholders as players. This game successfully addresses the stakeholders' preferences in a functional outcome-focused way, resolving the high indeterminacy of the alternative designs through a cooperative game. At the same time, their strategic interactions are captured in a process-focused non-cooperative game. Hence, the optimal design is identified through the simultaneous employment of the Nash bargaining solution and the Nash equilibrium.i

show abstract

“…Alternatively, the geometric mean is also used in AHP and fuzzy AHP techniques (Lai, Wong and Cheung 2002), (Kim andSong 2009), and(Carnero 2013). In an ordinal ranking, the individuals' preferences can also be aggregated (Hurley and Lior 2002) and quite often the preferential differences among different alternatives and priorities are also considered/weighted to obtain the group utility values (Huang et al 2013). Dijkstra (2013) presented a method for the extraction of group weighting factors from the group members' AHP pairwise comparison matrices, minimizing the inconsistencies introduced in the group preference synthesizing.…”

Section: Group Decision Makingmentioning

confidence: 99%

Value modelling for multi-stakeholder and multi-objective optimisation in engineering design

Papageorgiou

Eres

Scanlan

2016

Journal of Engineering Design

View full text Add to dashboard Cite

The work presented culminates in the development of a value model used in the conceptual phase of engineering design, with the preferences of more than one stakeholder addressed in the Multi-Stakeholder and Multi-Objective Optimization. The "value" of proposed solutions is assessed in an objective way both from performance and economic perspectives, while the optimal solution is identified based on the needs of the user and manufacturer, as major stakeholders. This novel value model for consistent value assessment synthesizes the multiattribute value/utility analysis with the Game Theory and Analytic Hierarchy Process (AHP) assessment methodologies. During the multi-criteria decision analysis, the deficiencies, introduced by the arbitrary numerical scales used in AHP to convert the linguistic preferences of the user between the various attributes to numerical values, are resolved. The preferences of a group of experts/decision makers are synthesized in the group value model through the extraction of weighting factors from the individuals' AHP pairwise comparison matrices. Moreover, Game Theory is used in a hybrid cooperative/bargaining, non-cooperative non-zero sum game between the stakeholders as players, identifying the optimal design through the simultaneous employment of the Nash bargaining solution and the Nash equilibrium.

show abstract

Aggregation of utility-based individual preferences for group decision-making

Cited by 92 publications

References 42 publications

A group package recommender based on learning group preferences, multi-criteria decision analysis, and voting

A group package recommender based on learning group preferences, multi-criteria decision analysis, and voting

Development and application of a value driven design assessment framework to an unmanned air system design

Value modelling for multi-stakeholder and multi-objective optimisation in engineering design

Contact Info

Product

Resources

About