An index for ordering fuzzy numbers

Choobineh, F.; Li, Huishen

doi:10.1016/0165-0114(93)90374-q

Cited by 176 publications

(66 citation statements)

References 5 publications

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“…Different fuzzy ordering techniques can be found in Yager (1981), Chen (1985), Yuan (1991), Choobineh and Li (1993), Fortemps and Roubens (1996), Wang and Kerre (2001a;2001b).…”

Section: Identification Of Motivated Employeesmentioning

confidence: 99%

An algorithm to identify the most motivated employees

Dáros

2013

Management Decision

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PurposeIn this paper, the aim is to present an algorithm to identify the most motivated employees according to the corporate human resources policies applied in a knowledge‐based company.Design/methodology/approachFirst, the author presents a complete table with motivation factors found in the literature. Then, a fuzzy tool, i.e. an adequacy index, is used in order to include subjectivity and uncertainty from personal perceptions both from employees and managers in the model.FindingsAn algorithm to identify the most motivated employees according to corporate motivation policies designed by managers is found.Practical implicationsResults provide information that can be used as a support for helping managers in decision making about training, promotion, leadership practices or team management.Originality/valueAn exhaustive list that does not exist in the literature about motivation factors is presented as well as the proposal of measure and identification on most‐motivated employees is also a new idea.

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“…Different fuzzy ordering techniques can be found in Yager (1981), Chen (1985), Yuan (1991), Choobineh and Li (1993), Fortemps and Roubens (1996), Wang and Kerre (2001a;2001b).…”

Section: Identification Of Motivated Employeesmentioning

confidence: 99%

An algorithm to identify the most motivated employees

Dáros

2013

Management Decision

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“…Based on [33], the loci of the left or right spreads and the maximum and minimum barriers of the α-cut of the fuzzy number, X, are µ L Xα (x) and µ R Xα (x), 0 ≤ α ≤ h X , respectively, where h X is the height. If X α is denumerable or connected, then:…”

Section: Action Selection Methodsmentioning

confidence: 99%

“…The index of optimism σ [34], is used to represent the level of uncertainty of the virtual environment. When selecting one particular action from a range of possible actions, the selection is based on the Hurwicz criterion [33] which is defined as: …”

Section: Action Selection Methodsmentioning

confidence: 99%

A Fuzzy Action Selection Method for Virtual Agent Navigation in Unknown Virtual Environments

Jaafar

McKenzie

Smaill

2007

2007 IEEE International Fuzzy Systems Conference

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This paper presents an action selection method using fuzzy logic. The objective is to solve behaviour conflict in behaviour-based architectures for virtual agent navigation in unknown virtual environments. Two main problems have been identified: how to decide which behaviour should be activated at each instant; and how to combine the results from different behaviours into one action. The method uses fuzzy α-levels to compute behaviour weight for each behaviour and the final action is selected using the Huwicz criterion. The results clearly demonstrate the mapping of inputs to output with a near-optimum path in every navigation task.

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“…Procedures for rank ordering the fuzzy numbers expressing aggregate performance have been considered by Jain (1977), Baldwin and Guild (1979), Bortolan and Degani (1985), Chen (1985), Yager (1981), Kaufmann and Gupta (1988), Buckley and Chanas (1989), Kim and Park (1990), Liou and Wang (1992b) and Choobineh and Li (1993). There are no completely acceptable methods.…”

Section: Annex 4 Ranking Fuzzy Numbersmentioning

confidence: 99%

Fuzzy applications in project appraisal: Part 2 fuzzy numbers

Smith

1994

Project Appraisal

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An index for ordering fuzzy numbers

Cited by 176 publications

References 5 publications

An algorithm to identify the most motivated employees

An algorithm to identify the most motivated employees

A Fuzzy Action Selection Method for Virtual Agent Navigation in Unknown Virtual Environments

Fuzzy applications in project appraisal: Part 2 fuzzy numbers

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