Models, Methods and Tools of Optimizing Costs for Development of Clusterized Organizational Structures in Construction Industry

  • Authors

    • M Mykytas
    • S Terenchuk
    • N Zhuravska
    2018-06-20
    https://doi.org/10.14419/ijet.v7i3.2.14414
  • clusterized organizational structure, economic and mathematical models, fuzziness, neuron network.
  • The mission of this research shall be studying the models and methods of evaluation of the expected costs to be used in economic efficiency optimization of clusterized organizational structures in construction industry. It comprises analysis of models and methods of simulation of the development of complex models under fuzzy conditions. It shows benefits and drawbacks of realizing the scenario approach based on econometric semi-linear dynamic equations. The optimization of costs has been proposed to be performed based on simulation modelling of various scenarios of development of clusterized organizational structures of construction branch. The results of simulation can be useful in feasibility demonstrations of the long-term plans and strategies of development on various stages of structures’ life cycle. The mathematical basics and scheme of forming the minimum costs for providing the best strategy of development of clusterized organizational structure.  The academic novelty of work consists in developing the rationale of application of fuzzy neuron boundaries. The responsibility for the development of fuzzy rules in order to form system fuzzy databases shall be vested in experts.

     

     

  • References

    1. [1] Palahniuk Y.V. ‘Transforming the financial instruments of cooperation between Ukraine and EU’, Proceedings of the Institute of Legislation of Verkhovna Rada of Ukraine, # 1, (2014), p. 99-105.

      [2] Murzin A., Anopchenko T. «Economic-Mathematical Modeling of Social and Environmental Risks Management of Projects of Urbanized Territories Development», Asian Social Science, 10(15), (2014), P. 249-254.

      [3] Kostenko O.V. ‘Defining the notion of ‘cluster’ from positions of systematic approach in economics’, International scientific journal ‘Innovative science’, # 9, (2015), p. 165-169.

      [4] Shinkareva L., Plahov A. «Not formalized methods of the analysis of risk of the investment project», Economic and humanitarian sciences, 4(219), ( 2010), Р. 8-11.

      [5] Nasirzadeh F., Khanzadi M., Rezaie M. «Dynamic modeling of the quantitative risk allocation in construction projects», International Journal of Project Management, 32(3), (2014), Р. 442-451.

      [6] Vass H. U., Timmer J., Kurths J. «Nonlinear dynamical systems identification and indirect measurements», Int. J Bif. Chaos, 14, (2004), P. 1903-1933.

      [7] McNelis, Paul D. «Neural network in finance: gaining predictive edge in the market», Elsevier Academic Press, (2005), 243p.

      [8] Che Ibrahim C. K. I., Costello S. B., & Wilkinson S. «Key indicators influencing the management of team integration in construction projects», International Journal of Managing Projects in Business, 8(2), (2015), P. 300-323.

      [9] http://www.worldcat.org/search?q=au%3AM+S+Sa%CC%81nchez&qt=hot_author">M S SaÌnchez, http://www.worldcat.org/search?q=au%3AH+Swierenga&qt=hot_author">H Swierenga, http://www.worldcat.org/search?q=au%3AL+A+Sarabia&qt=hot_author">L A Sarabia, http://www.worldcat.org/search?q=au%3AE+Derks&qt=hot_author">E Derks, http://www.worldcat.org/search?q=au%3AL+Buydens&qt=hot_author">L Buydens. «Performance of multi-layer feedforward and radial base function neural networks in classification and modeling», Chemometrics and Intelligent Laboratory Systems, 2 (199606), P. 101-119.

      [10] http://www.worldcat.org/search?q=au%3ABerlec%2C+Tomaz%CC%8C.&qt=hot_author">Tomaz Berlec, http://www.worldcat.org/search?q=au%3ASluga%2C+Alojzij.&qt=hot_author">Alojzij Sluga, http://www.worldcat.org/search?q=au%3AGovekar%2C+Edvard.&qt=hot_author">Edvard Govekar, et al. «Hybrid self-organization based facility layout planning», Strojnis ki vestnik, 60(12), (2014), Р. 789-796.

      [11] Blum, C., Puchinger J., Raid, J.R., Roli A. «Hybrid metaheuristics in combinatorial optimization: A survey», Applied Soft Computing, 11(6), (2011), P. 4135-4151.

      [12] Hammah, R. «Fuzzy cluster algorithm for the automatic identification of joint sets», International Journal of Rock Mechanics and Mining Science, 35(7), (2010), P. 889-905.

      [13] Terenchuk S., Yeremenko B., Kartavykh S., Nasikovsky O. «Application of fuzzy mathematics methods to processing geometric parameters of degradation of building structures», Eureka: physics and engineering», 1, (2018), P.56-62.

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    Mykytas, M., Terenchuk, S., & Zhuravska, N. (2018). Models, Methods and Tools of Optimizing Costs for Development of Clusterized Organizational Structures in Construction Industry. International Journal of Engineering & Technology, 7(3.2), 250-254. https://doi.org/10.14419/ijet.v7i3.2.14414