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COMBINED METHOD OF RANKING OPTIONS IN PROJECT DECISION SUPPORT SYSTEMS

Authors: Beskorovainyi, V.;

COMBINED METHOD OF RANKING OPTIONS IN PROJECT DECISION SUPPORT SYSTEMS

Abstract

The subject of research in the article is the process of ranking options in project decision support systems. The goal of the work is to create a method for ranking options to improve the efficiency of decision support systems by coordinating the interaction between automatic and interactive procedures of computer-aided design systems. The following tasks are solved in the article: review and analysis of the current state of the problem of ranking options in design decision support systems; decomposition of the problem of project decision support; development of a combined method of ranking options, which combines the procedures of technologies of ordinalistic and cardinalistic ordering; development of a method of minimax selection of options from a set of effective for the procedure of expert evaluation. The following methods are used: systems theory, utility theory, optimization and operations research. Results. As a result of the analysis of the modern methodology of decision support, the existence of the problem of correct reduction of subsets of effective design options for ranking, taking into account factors that are difficult to formalize, knowledge and experience of the decision maker (DM), has been established. The decomposition of the problem of supporting the making of design decisions into the tasks of determining the goal of designing an object, forming a universal set of design decisions, identifying sets of admissible and effective decisions, ranking and choosing the best design option for decision makers has been performed. A combined method for ranking options has been developed, which combines the procedures of ordinalistic and cardinalistic ordering technologies and allows you to correctly reduce subsets of effective design solutions for ranking decision makers. A method of minimax selection of options from a set of effective ones for the expert evaluation procedure of decision makers has been developed, which allows improving the quality of the assessment. Conclusions. The developed method expands the methodological foundations of automation of processes for supporting multi-criteria design decisions, allows for the correct reduction of the set of effective alternatives for the final choice, taking into account factors that are difficult to formalize, knowledge and experience of decision makers. The practical use of the results obtained due to the proposed procedure for determining the set of effective solutions will reduce the time and capacitive complexity of decision support, and due to the use of the maximin procedure for selecting options in the synthesis of the estimation model – to improve the quality of design solutions.

Keywords

330, design automation; multicriteria evaluation; effective solutions; comparative identification; project decision support; utility theory, effective solutions, TA177.4-185, 620, Engineering economy, project decision support, design automation, comparative identification, автоматизация проектирования; многокритериальная оценка; эффективные решения; компараторна идентификация; поддержка принятия проектных решений; теория полезности, multicriteria evaluation, utility theory, автоматизація проєктування; багатокритеріальне оцінювання; ефективні рішення; компараторна ідентифікація; підтримка прийняття проєктних рішень; теорія корисності

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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