Modification of analytic hierarchy process to enhance decisions made objectivity

System analysis, control and data processing


Solovjeva I. A.1*, Solovjev D. S.2**, Litovka Y. V.1***, Korobova I. L.1****

1. Tambov State Technical University, 106, Sovetskaya, Tambov, 392000, Russia
2. Tambov State University named after G.R. Derzhavin, 33, Internatsional'naya, Tambov, 392000, Russia



Units and components of aviation technology are subjected to corrosion processes while in service. Galvanic coatings are employed to repair parts, damaged by corrosion, and improve their protective and decorative characteristics.

The problems emerging while preparing electroplating industries relate to the class of weakly structured and multi-criteria problems, in a number of cases not subjected to formalization whatsoever. Thus, the solution of these problems can be obtained employing the intuition, experience and knowledge of the person making the decision. To solve these problems, decision support systems based on user and computer dialogue using artificial neural networks, production fuzzy models of knowledge and genetic algorithms are already being employed. In its turn, there are no works aimed at finding solutions to the emerging problems using methods of decision theory. The authors give preference to the analytic hierarchy process for solving the problems under consideration due to its universality. However, this method is not devoid of subjectivity in evaluating the alternatives in question when choosing a solution. The authors suggest a modification of the traditional analytic hierarchy process, which is aimed at reducing the share of experts participation in the decision making process. It is assumed, that some of the criteria by which alternatives are evaluated are given numerically. The authors suggest evaluate alternatives by such criteria as the ratio of their values, which allows get rid of the 9-point scale. When calculating weight factors, a function is introduced that returns 1 or —1, depending on the criterion minimization or maximization, to match the best alternative of the considered criterion to the maximum weighting factor. In this case, the calculations of the consistency index and the consistency relation become unnecessary. These innovations make allow exclude an expert when assessing a significant amount of quantitative data and, consequently, avoid variants of the estimates mismatch. This, in turn, makes the decision-making process more objective and fast. The effectiveness of the proposed modification of the analytic hierarchy process is compared by the example of decision-making on the selection of coating metal taking into account physical, mechanical, economic, environmental and technological factors. For the example under consideration, the expert was excluded from 180 comparisons.


decision making, modified analytic hierarchy process, multi-criteria problem, objective choice, weighting factors


  1. Schwinn D.B. Coupling of static and dynamic fuselage design, Aircraft Engineering and Aerospace Technology: An International Journal, 2016, vol. 88, no. 1, pp.1 – 15.

  2. Miguel M., Silva C.E.A., Peres M.P., Voorwald H.J.C. Study of influence of zinc-nickel and cadmium electroplated coatings on fatigue strength of aeronautical steels, Fatigue, 2002, pp. 15 – 23.

  3. Davarpanah A., Hemat Ah., Larki M. Coating Removal Techniques in Aerospace Industries: Study Case // Journal Powder Metall. 2017. Min 6: 155 DOI: 10.4172/2168-9806.1000155. URL:

  4. Denker I.I., Vladimirskii V.N. Tekhnologiya okraski samoletov i vertoletov grazhdanskoi aviatsii (Technology of civil airplanes and helicopters painting), Moscow, Mashinostroenie, 1988, 128 p.

  5. Popovich V.A., Gamburg Yu.D., Serdyuchenko N.A., Belimenko G.S, Yamnova T.P. Elektrokhimiya, 1992, vol. 28, no. 3, pp. 333 – 342.

  6. Solov’eva N.D. Frolova I.I., Legkaya D.A. Kondensirovannye sredy i mezhfaznye granitsy, 2014, vol. 16, no 2, pp. 201 – 205.

  7. Garich H., Gebhart L., Taylor E.J., Inman M., McCrabb H. Development and Characterization of Plating Cell Geometry for Printed Circuit Board and Packaging Applications, ECS Transactions, 2017, vol. 3 (16), pp. 1 – 10.

  8. Ishkulova A.R. Analiz konstruktivnykh osobennostei anodov dlya naneseniya gal’vanicheskikh pokrytii, Theoretical & Applied Science, 2013, vol. 10(6), pp. 45 – 48.

  9. Protalinskij O.M., Litovka Ju.V., Pashkevich A.A. Datchiki i sistemy, 2009, no. 5, pp. 35 – 36.

  10. Sánchez Lasherasa F., Vilán Vilánb J.A., García Nietoc P.J., del Coz Díazd J.J. The use of design of experiments to improve a neural network model in order to predict the thickness of the chromium layer in a hard chromium plating process, Mathematical and computer modeling, 2010, vol. 52, no. 7 – 8, pp. 1169 – 1176.

  11. Zhang J., Zheng Z., Qu Y., You L., Wang S., Li L. pH Fuzzy control of automated industrial electroplating of gold, Chemical & Engineering Technology, 1997, vol. 20, no. 8. pp. 576 – 580.

  12. Mon E. Ossman, Walaa Sheta, Eltaweel Y. Linear Genetic Programming for Prediction of Nickel Recovery from Spent Nickel Catalyst, American J. of Engineering and Applied Sciences, 2010, 3 (2), pp. 482 — 488.

  13. Podinovskij V.V., Nogin V.D. Pareto-optimal’nye reshenija mnogokriterial’nyh zadach (Pareto-optimal solutions of multicriteria problems), Moscow, Fizmatlit, 2007, 256 p.

  14. Miettinen K. Nonlinear Multiobjective Optimization, Boston, Kluwer Academic Publisher, 1999, 293 p.

  15. Kini R.L., Rajfa H. Prinjatie reshenij pri mnogih kriterijah: predpochtenija i zameshhenija (Decision-making under many criteria: preferences and substitutions), Moscow, Radio i svjaz’, 1981, 560 p.

  16. Saati T.L. Prinjatie reshenij. Metod analiza ierarhij (Decisions Making. Analytic Hierarchy Process), Moscow, Radio i svjaz’, 1993, 316 p

  17. Red’ko A.O., Smerchinskaja S.O., Jashina N.P. Trudy MAI, 2016, no. 85, available at:

  18. Kolesnikova S.I. Prikladnaja diskretnaja matematika, 2009, 4 (6), pp. 102 – 109.

  19. Dubrovin V.I., Mironova N.A. Iskusstvennyj intellect, 2009, no, 3, pp. 464 – 470.

  20. Solov’ev D.S., Mukina I.A., Litovka Ju.V. Svidetel’stvo o gosudarstvennoj registracii programmy dlja JeVM v FIPS № 2017618189, 25.07.2017.

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