Human Behavior in a Multi-Criteria Choice Problem With Individual Tasks of Different Difficulties

Furems, E. M.; Larichev, Oleg I.; Roizenson, G. V.; Лотов, А. В.; Miettinen, Kaisa

doi:10.1142/s0219622003000501

Cited by 15 publications

(2 citation statements)

References 6 publications

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“…Some types of information lacked corresponding research. Additional types of admissible information elicitation types were introduced later (see, e.g., [9,10]).…”

Section: Use Language For Problem Description That Is Natural To the mentioning

confidence: 99%

Verbal Decision Analysis: Foundations and Trends

Moshkovich

Mechitov

2013

Advances in Decision Sciences

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The primary goal of research in multiple criteria decision analysis is to develop tools to help people make more reasonable decisions. In many cases, the development of such tools requires the combination of knowledge derived from such areas as applied mathematics, cognitive psychology, and organizational behavior. Verbal Decision Analysis (VDA) is an example of such a combination. It is based on valid mathematical principles, takes into account peculiarities of human information processing system, and fits the decision process into existing organizational environments. The basic underpinnings of Verbal Decision Analysis are demonstrated by early VDA methods, such as ZAPROS and ORCLASS. New trends in their later modifications are discussed. Published applications of VDA methods are presented to support the findings.

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“…Some types of information lacked corresponding research. Additional types of admissible information elicitation types were introduced later (see, e.g., [9,10]).…”

Section: Use Language For Problem Description That Is Natural To the mentioning

confidence: 99%

Verbal Decision Analysis: Foundations and Trends

Moshkovich

Mechitov

2013

Advances in Decision Sciences

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“…Investors make a choice among different investment alternatives. Furems et al 1 present the results of a laboratory study of human behavior in this problem. The first studies about choice problem go back to the ElectreI method by Roy.…”

Section: Introductionmentioning

confidence: 99%

Integrating Prometheeii With the Tchebycheff Function for Multi Criteria Decision Making

Soylu

2010

Int. J. Info. Tech. Dec. Mak.

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Choice problem is related to finding the best compromise alternative or a set of alternatives among various options by considering conflicting criteria. PrometheeII is one of the well-known decision making methods that has been successfully applied to this problem. However, both our experiments and the other results from literature show that the PrometheeII algorithm performs better especially for problems having convex frontier. In this study, PrometheeII is integrated with the Tchebycheff function, which is capable of reaching efficient alternatives located at non-convex part of the efficient frontier. An experimental study is performed on the integrated procedure, PrometheeII and the multiplicative version of PrometheeII by using different test problems from the multi objective optimization literature.

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UniComBOS—Intelligent Decision Support System for multi‐criteria comparison and choice

Ashikhmin

Furems

2005

Multi Criteria Decision Anal

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This paper discusses the main ideas of a new approach to discrete multi‐criteria comparison and choice from a small set of alternatives and its implementation as the Intelligent Decision Support System (IDSS) UniComBOS. The approach has been developed within the Verbal Decision Analysis paradigm. While seeking to use psychologically correct information on a decision maker's (DM's) preferences, the approach allows to take into account the individual DM's ability to deal with multi‐criteria alternatives. This is facilitated by a special graphical user interface, using colour differentiation of preferences, which assists a DM in making comparisons and provides the possibility for additional checks on the consistency of her/his answers. As in most multi‐criteria decision‐making aids, multi‐criteria descriptions of the alternatives are decomposed into their parts upon the least possible number of criteria (‘units’). The DM makes pair‐wise comparison starting from single‐criterion ‘units’, and then the number of criteria in a ‘unit’ is incremented one‐by‐one, until either the best alternative is found by the newly introduced rule of U‐Dominance, or it is obvious that the comparison of the given multi‐criteria ‘units’ poses a great challenge to the DM. In the latter case, the system would not be able to find the single best alternative, but it will indicate a set of alternatives that are incomparable with each other and that are preferable for DM in comparison to any alternative not included in this set. Copyright © 2006 John Wiley & Sons, Ltd.

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Human Behavior in a Multi-Criteria Choice Problem With Individual Tasks of Different Difficulties

Cited by 15 publications

References 6 publications

Verbal Decision Analysis: Foundations and Trends

Verbal Decision Analysis: Foundations and Trends

Integrating Prometheeii With the Tchebycheff Function for Multi Criteria Decision Making

UniComBOS—Intelligent Decision Support System for multi‐criteria comparison and choice

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