Verbal Decision Analysis Methods Research Articles

Побудова мультиплікативно-адитивної згортки критеріїв в просторі кількі-сних і якісних показників для визначення пріоритетності проєктів

One of the main problems in scientific activity organization on a competitive basis is to improve methods of R&D project evaluation and priority determination. The project priority level may be determined using approaches based on the multi-attribute utility theory (MAUT), whose development is the subject matter of many studies and publications. Despite of the large number of publications on the subject, the development of a scientifically substantiated mathematical apparatus for multicriteria project evaluation is still a topical and challenging problem. The complexity of the development of project priority determination methods is due to difficulties in the construction of a unified rating scale that would allow one to measure the value of project indices differing in physical content and dimension. That is, what is difficult is the structurization of a decision-making person (DMP)’s preferences and the formalization of preference evaluation. It is also difficult to construct a criterion-target model that would adequately represent the system of DMP preferences in the form of a scalar value function, which is termed a criteria convolution, an integral criterion, or an integral value function (IVF). MAUT-based computational algorithms widely use procedures of common criteria scaling, in which one quality index is replaced with another. Such algorithms have a resolution equal to one; however, they operate with quantitative criteria alone, thus significantly narrowing their application area. Another drawback of theirs is the lack of simple methods to determine the value function at indifference (DMP preference equality) points. The aim of this work is to eliminate these drawbacks in a multiplicative-additive IVF model. To do this, the following was done. Functional relationships between DMP preferences and alternative quality indices were established to give analytical expressions for evaluating local value functions at indifference points. A method was developed for constructing a multiplicative-additive criteria convolution to evaluate and rank alternatives in the space of quantitative and qualitative indices. An algorithm was developed to determine the priority of projects; the algorithm allows one to rank alternatives with a resolution equal to one. In this work, decision theory, multicriteria utility theory, and verbal decision analysis methods were used. The results obtained may be used in R&D efficiency evaluation, competitive project selection, and space program formation in the rocket space industry.

Selection and Prioritization of Software Requirements Applying Verbal Decision Analysis

During the software development process, the decision maker (DM) must master many variables inherent in this process. Software releases represent the order in which a set of requirements is implemented and delivered to the customer. Structuring and enumerating a set of releases with prioritized requirements represents a challenging task because the requirements contain their characteristics, such as technical precedence, the cost required for implementation, the importance that one or more customers add to the requirement, among other factors. To facilitate this work of selection and prioritization of releases, the decision maker may adopt some support tools. One field of study already known to solve this type of problem is the Search‐Based Software Engineering (SBSE) that uses metaheuristics as a means to find reasonable solutions taking into account a set of well‐defined objectives and constraints. In this paper, we seek to increase the possibilities of solving the Next Release Problem using the methods available in Verbal Decision Analysis (VDA). We generate a problem and submit it so that the VDA and SBSE methods try to resolve it. To validate this research, we compared the results obtained through VDA and compared with the SBSE results. We present and discuss the results in the respective sections.

Selection of a faculty member in academia: a case for verbal decision analysis

Personnel selection problem is often viewed as a multi criteria problem and there are many examples when different multi criteria techniques support the process. The multi criteria approach was used in several studies of faculty selection in academia but not many recognised that there were peculiarities in the selection process. Most studies concentrated on rank ordering of a small number of finalists while one of the main tasks of the search committee in academia is to select a smaller number of candidates from a possibly large pool of applicants for a more thorough review. In our paper we propose a three-step approach to the problem and recommend verbal decision analysis (VDA) as a tool. Using a VDA method provides a reliable preference elicitation process and the decision rules are easy to understand and explain. Free tool ORCON_Z helps with the practical application. The proposed procedure was well received by the participants and provided valuable information during the selection process.

ARACE – A New Method for Verbal Decision Analysis

ARACE is a new method developed within the framework of Verbal Decision Analysis (VDA). VDA methods work with verbal form of preference elicitation and evaluation of alternatives without resorting to numbers. ARACE is based on the ideas of the VDA method ZAPROS but uses a more flexible approach to inconsistency of the decision-maker's preferences by introducing a special construct of a "quasi-expert." Mismatched preferences of the decision-maker are viewed as preferences of several quasi-experts. The preference system for each quasi-expert is transitive, leading to consistent decision rules formed for each quasi-expert separately. These rules are used to compare alternatives. Differences in possible comparison of alternatives based on different quasi-experts are resolved through a Clustered Rankings Method for rankings with ties.

Verbal Decision Analysis: Foundations and Trends

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.

Dealing the Selection of Project Management through Hybrid Model of Verbal Decision Analysis

The decision may be defined as a result of a process of choice, given an identified problem or when the decision maker faces an opportunity of creation, optimization or improvement in an environment. Considering that agile methodologies, in focus Framework SCRUM, are always more popular in Development Software Companies, and noticing that the mentioned companies cannot always apply every characteristics of the framework, this paper presents an hybrid application of methodologies from Verbal Decision Analysis (VDA) framework to select some of the SCRUM approaches to be applied in the company, considering the elicitation of preferences of a decision maker. The work intends to provide an evaluation of Project Management approaches applied in the Software Development and examine them toward to identify which are the most preferable ones, aided by the application of a hybrid model of decision making. The hybrid model aims at classifying alternatives using ORCLASS method, through the developed software, and ranking them using a Verbal Decision Analysis method (ZAPROS III-i). Afterward, Specific Practices (SP) of Capability Maturity Model Integration (CMMi) level 2 were chosen, and approaches to attend the SP's were ranked from the most preferable to the least preferable ones, aiming to help enterprises which are not able to reach a complete CMMi qualification.

Verbal ordinal classification with multicriteria decision aiding

Professionals in neuropsychology usually perform diagnoses of patients’ behaviour in a verbal rather than in a numerical form. This fact generates interest in decision support systems that process verbal data. It also motivates us to develop methods for the classification of such data. In this paper, we describe ways of aiding classification of a discrete set of objects, evaluated on set of criteria that may have verbal estimations, into ordered decision classes. In some situations, there is no explicit additional information available, while in others it is possible to order the criteria lexicographically. We consider both of these cases. The proposed Dichotomic Classification (DC) method is based on the principles of Verbal Decision Analysis (VDA). Verbal Decision Analysis methods are especially helpful when verbal data, in criteria values, are to be handled. When compared to the previously developed Verbal Decision Analysis classification methods, Dichotomic Classification method performs better on the same data sets and is able to cope with larger sizes of the object sets to be classified. We present an interactive classification procedure, estimate the effectiveness and computational complexity of the new method and compare it to one of the previously developed Verbal Decision Analysis methods. The developed and studied methods are implemented in the framework of a decision support system, and the results of testing on artificial sets of data are reported.

The possibilities of verbal decision analysis methods for construction solutions

Due to high cost of mistakes in investment choice problems, such a choice should be well founded. This paper presents an overview of existing methods for choosing the best object and a new multi-criteria method called Scale of Normalised and Ordered Differences (SNOD) basing on Verbal Decision Analysis (VDA) approach. The possibility of criteria interdependence is taken into account. The method was evaluated by statistical modelling. The method has been applied for practical cases in Vilnius. Risk is an integral element of any economical work. It must be estimated and minimised. The method SNOD can be applied to determining investments risk in construction.

VERBAL DECISION MAKING ANALYSIS

The paper presents the ideology of a qualitative approach to decision making ‐ verbal decision analysis. The authors have analyzed existing quantitative approaches and pointed out their main disadvantages. They formulated the requirements for decision‐making methods taking into account these disadvantages: psychological correctness of a dialog with decision maker (DM), strict mathematical proof of the methods and checking of DM information for consistency. The authors present the results of research on psychological correctness of operations of preference elicitation from DM. Several existing verbal decision analysis methods are briefly mentioned.

Method ZAPROS for Multicriteria Alternatives Ranking and the Problem of Incomparability

The new method for the construction of partial order on the set of multicriteria alter- natives is presented. This method belongs to the family of Verbal Decision Analysis methods and gives a more efficient means of problem solution. The method is based on psychologically valid op- erations for information elicitation from a decision maker: comparisons of two distances between the evaluations on the ordinal scales of two criteria. The information received from a decision maker is used for the construction of a binary relation between a pair of alternatives which yields preference, indifference and incomparability relations. The notion of a method decisive power is introduced. The illustrative example is given.