The main advantages of separable programming for multidimensional problems

Abstract

An essential component of innovative technologies in the theory of information measuring systems (IMS) and in their computer-aided design systems should be the result of solving problems of improving efficiency, optimizing systems and their functional elements on sets of structures, signals and parameters for the vector of quality indicators presented in tactical and technical requirements, using cost indicators. These results can be obtained through solving the problems of system analysis, finding the links between the quality index of IMS and the technical parameter vector, determining the problems of fuzziness, volatility of cost indicators, taking into account the multidimensionality of problems, as requirements for the adequacy of the mathematical and physical model of IMS, etc. But at the same time in a large number of such algorithms there is such an important link, which largely determines their implementation and quality. This is the choice of the best method for such problems, which are usually formulated in the form of mathematical programming. The paper shows that this method can be separable programming, which gives significant advantages over other methods. Numerous publications of optimization problems of IMS of different assignments and their functional elements on this topic [1-5] confirm the possibility of using the proposed method.

Authors and Affiliations

G. Aloshin

Keywords

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  • EP ID EP497856
  • DOI 10.18664/ikszt.v0i6.119914
  • Views 147
  • Downloads 0

How To Cite

G. Aloshin (2017). The main advantages of separable programming for multidimensional problems. Інформаційно-керуючі системи на залізничному транспорті , 22(6), 3-8. https://europub.co.uk/articles/-A-497856