COMBINED METHOD OF RANKING OPTIONS IN PROJECT DECISION SUPPORT SYSTEMS

Keywords: design automation, multicriteria evaluation, effective solutions, comparative identification, project decision support, utility theory

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.

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Author Biography

Vladimir Beskorovainyi, Kharkiv National University of Radio Electronics
Doctor of Sciences (Engineering), Professor, Professor of the Department of System Engineering

References

Kossiakoff, A., Sweet, W. N., Seymour, S. J., Biemer, S. M. (2011), Systems Engineering Principles and Practice, Hoboken, New Jersey : A John Wiley & Sons, 599 p.

Timchenko, A. A. (2004), Fundamentals of system design and analysis of complex objects: Fundamentals of system approach and system analysis of objects of new technology [Osnovy systemnoho proektuvannya ta analizu skladnykh ob'yektiv: Osnovy systemnoho pidkhodu ta systemnoho analizu ob'yektiv novoyi tekhniky], Ed. by Yu. G. Legi, Kyiv, Lybid, 288 p.

Greco, S., Ehrgott, M., Figueira, J. R. (2016), Multiple Criteria Decision Analysis – State of the Art Surveys, New York : USA, Springer, 1346 p.

Kaliszewski, I., Kiczkowiak, T., Mirofori-dis, J. (2016), "Mechanical design, Multiple Criteria Decision Making and Pareto optimality gap", Engineering Computations, Vol. 33 (3), P. 876–895.

Putyatin, V. G. (2015), "Choosing a rational option for the technical implementation of a complex organizational and technical system in the context of multi-criteria" ["Vibor ratsional'nogo varianta tekhnicheskoy realizatsii slozhnoy organizatsionno-tekhncheskoy sistemi v usloviyakh mnogokriterial'nosti"], Restratsіya, zberіgannya and і obrobka danih, Vol. 17, No. 4, P. 71–92.

Beskorovainyi, V. V. (2002), "Systemological analysis of the problem of structural synthesis of geographically distributed systems" ["Sistemologicheskiy analiz problemy strukturnogo sinteza territorial'no raspredelennykh sistem"], Automated control systems and automation devices, Issue 120, P. 29–37.

Beskorovainyi, V., Kuropatenko, O., Gobov, D. (2019), "Optimization of transportation routes in a closed logistics system", Innovative Technologies and Scientific Solutions for Industries, No. 4 (10), P.24–32. DOI: https://doi.org/10.30837/2522-9818.2019.10.024

Under total. ed. Vasilieva, S. N., Zvirkuna, A. D. (2019), "Managing the Development of Large-Scale Systems" ["Upravleniye razvitiyem krupnomasshtabnykh sistem"], Proceedings of the 12th Int. Conference (MLSD'2019), 1-3 Oct. 2019, Moscow, IPU RAN, 1294 p.

Yelizyeva, A., Artiukh, R., Persiyanova, E. (2019), "Target and system aspects of the transport infrastructure development program", Innovative Technologies and Scientific Solutions for Industries, No. 3 (9), P. 81–90. DOI: https://doi.org/10.30837/2522-9818.2019.9.081

Kosenko, V., Gopejenko, V., Persiyanova, E. (2019), "Models and applied information technology for supply logistics in the context of demand swings", Innovative Technologies and Scientific Solutions for Industries, No. 1 (7), P. 59–68. DOI: https://doi.org/10.30837/2522-9818.2019.7.059

Petrov, K. E., Deineko, A. A., Chalaya, O. V., Panferova, I. Y. (2020), "Method of ranking options in the procedure of collective expert evaluation" ["Metod ranzhyrovanyya variantiv pry provedenyy protsedury kollektyvnoho ékspertnoho otsenyvanyya"], Radioelectronics, Informatics, Management, No. 2, P. 84–94.

Bernasconi, M., Choirat, C., Seri, R. (2014), "Empirical properties of group preference aggregation methods employed in AHP: Theory and evidence", European Journal of Operational Research, No. 232, P. 584–592.

Podolyaka, O. A., Podolyaka, A. N. (2015), "Application of ordinal normalization and scrambling of criteria for solving multicriteria problems" ["Prymenenye poryadkovoy normalyzatsyy y skremblyrovanyya kryteryev dlya reshenyya mnohokryteryalʹnykh zadach"], Automotive and Electronics. Modern technologies, No. 8, P. 60–69.

Ataei, M., Shahsavany, H., Mikaeil, R. (2013), "Monte Carlo Analytic Hierarchy Process (MAHP) approach to selection of optimum mining method", International Journal of Mining Science and Technology, No. 23, P. 573–578.

Bagočius, V., Zavadskas, E. K., Turskis, Z. (2014), "Multi-person selection of the best wind tur-bine based on the multi-criteria integrated additive-multiplicative utility function", Journal of Civil Engineering and Management, No. 20, P. 590–599.

Baky, I. A. (2014), "Interactive TOPSIS algorithms for solving multi-level non-linear multi-objective decision-making problems", Applied Mathematical Modelling, No. 38, P. 1417–1433.

Baky, I., Abo-Sinna, M. (2013), "ATOPSIS for bi-level MODM problems", Applied Mathematical Modelling, No, 37, P. 1004-1015.

Vilkas, E. Y., Mayminas, E. Z. (1981), Solution: theory, information, modeling [Resheniye: teoriya, informatsiya, modelirovaniye], Moscow : Radio and Communication, 328 p.

Petrov, E. G., Brynza, N. A., Kolesnik, L. V., Pisklakova, O. A. (2014), Methods and models of decision making in conditions of multicriteria and uncertainty [Metody i modeli prinyatiya resheniy v usloviyakh mnogokriterial'nosti i neopredelennosti], Kherson : Grin D. S., 192 p.

Beskorovainyi, V., Berezovskyi, G. (2017), "Estimating the properties of technological systems based on fuzzy sets", Innovative Technologies and Scientific Solutions for Industries, No. 1 (1), P. 14–20. DOI: https://doi.org/10.30837/2522-9818.2017.1.014

Beskorovainyi, V., Podolyaka, K. (2015), "Modifications of the directed search method for reengineering the topological structures of large-scale monitoring systems" ["Modifikatsii metoda napravlennogo perebora dlya reinzhiniringa topologicheskikh struktur sistem krupnomasshtabnogo monitoringa"], Radioelectronics and Informatics, No. 3 (70), P. 55–62.

Beskorovainyi, V., Petryshyn, L, Shevchenko, O. (2020), "Specific subset effective option in technology design decisions", Applied Aspects of Information Technology, Vol. 3, No. 1, P. 443–455.

Bezruk, V. M., Chebotareva, D. V., Skorik, Yu. V. (2017), Multicriteria analysis and choice of telecommunication means [Mnogokriterial'nyy analiz i vybor sredstv telekommunikatsiy], Kharkiv : Ukraine, FOP Koryak S. F., 268 p.

Deb, K., Deb, D. (2014), "Analysing mutation schemes for real-parameter genetic algorithms", International Journal of Artificial Intelligence and Soft Computing, No. 4 (1), Р. 1–28.

Deb, K., Himanshu, J. (2014), "An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: Solving problems with box constraints", IEEE Trans. Evolutionary Computation, No. 18 (4), Р. 577–601.

Kalyanmoy, D. (2011), "Multi-objective optimization using evolutionary algorithms: an introduction", In Multi-objective evolutionary optimization for product design and manufacturing, Springer, Р. 3–34.

Mikhalevich, V. S., Volkovich, V. L. (1982), Computational methods of research and design of complex systems [Vychislitel'nyye metody issledovaniya i proyektirovaniya slozhnykh sistem], Moscow : Nauka, 288 p.

Beskorovainyi, V., Krasko, A. (2017), "Automation of processes for choosing effective solutions in the automated design of control and automation systems" ["Avtomatizatsiya protsessov vybora effektivnykh resheniy pri avtomatizirovannom proyektirovanii sistem upravleniya i avtomatiki"], Bulletin of the Kherson National Technical University, No. 4 (27), P. 208–212.

Deb, K., Pratap, A., Agarwal, S., Meyarivan, T. (2002), "A fast and elitist multiobjective genetic algorithm: NSGA-II", IEEE transactions on evolutionary computation, Vol. 6 (2), P. 182–197.

Shadura, O. (2019), "Modification of genetic algorithms based on the method of non-centered principal components and standard tests" ["Modyfikatsiya henetychnykh alhorytmiv na osnovi metodu netsetrovanykh holovnykh komponent ta standartni testy"], World Science, No. 4 (44), P. 4–11.

Bernasconi, M., Choirat, C., Seri, R. (2014), "Empirical properties of group preference aggrega-tion methods employed in AHP: Theory and evidence", European Journal of Operational Research, No. 232, P. 584–592.

Saaty, T. L. (2016), "The Analytic Hierarchy and Analytic Network Processes for the Measurement of Intangible Criteria and for Decision-Making", Multiple Criteria Decision Analysis. International Series in Operations Research & Management Science, New York : Springer, Vol. 233, P. 363–419.

Figueira J., Mousseau, V., Roy, B. (2016), "ELECTRE Methods", Multiple Criteria Decision Analysis. International Series in Operations Research & Management Science, New York : Springer, Vol. 233, P. 155–185.

Brans, J. P., De, S. Y. (2016), "PROMETHEE Methods Multiple Criteria Decision Analysis", International Series in Operations Research & Management Science, New York : Springer, Vol. 233, P. 187–219.

Papathanasiou, J., Ploskas, N. (2018), "TOPSIS", Multiple Criteria Decision Aid. Springer Optimization and Its Applications, Cham : Springer, Vol. 136, P. 1−30.

Beskorovainyi, V., Trofimenko, I. V. (2006), "Structural-parametric identification of multifactor estimation models" [Strukturno-parametrychna identyfikatsiya modeley bahatofaktornoho otsinyuvannya"], Weapons systems and military equipment, No. 3 (7), P. 56–59.

Beskorovainyi, V., Іmanhulova, Z. (2017), "Тechnology of large-scale objects system optimization", ECONTECHMOD, Vol. 06, No. 4, Р. 3–8.

Beskorovainyi, V., Berezovskyi, H. (2017), "Іdentification of preferences in decision support systems", ECONTECHMOD, Vol. 06, No. 4, Р. 15–20.

Beskorovainyi, V. (2017), "Parametric synthesis of models for multicriterial estimation of technological systems", Innovative Technologies and Scientific Solutions for Industries, No. 2 (2), P. 5–11. DOI: https://doi.org/10.30837/2522-9818.2017.2.005


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Published
2020-12-21
How to Cite
Beskorovainyi, V. (2020) “COMBINED METHOD OF RANKING OPTIONS IN PROJECT DECISION SUPPORT SYSTEMS”, INNOVATIVE TECHNOLOGIES AND SCIENTIFIC SOLUTIONS FOR INDUSTRIES, (4 (14), pp. 13-20. doi: 10.30837/ITSSI.2020.14.013.