2018. No. 3(45)

      For practical, important tasks in the fields of economics and logistics, as well as in a number of technical applications, it becomes necessary to solve the traveling salesman problem (TSP). Quite often, the features of these problems lead to the traveling salesman problem in asymmetric formulation (asymmetric traveling salesman problem, ATSP). Moreover, in some practical applications it is desirable to obtain an exact solution. One of the known exact algorithms for solving the ATSP is an algorithm that implements the well-known branch and bound method. The known experimental estimates of its complexity on the average are exponential. However, this does not mean that for small dimensions of the problem (currently, no more than 70–75), the expected time for solving the individual problem is unacceptably high. The need to reduce the time for solving individual problems dictated by practice is associated with the use of various modifications of this algorithm, of which a modification that involves storing truncated matrices in the search decision tree is one of the most effective. In this article, the authors rely on this modification. Other possible improvements in the time efficiency of the software implementation of the branch and bound method are related, among other things, to obtaining the initial approximation by heuristic algorithms. As a result, we get a combined algorithm, in which, at the first stage, some heuristics works to obtain the initial solution, from which the branch and bound method starts. This idea has been discussed for a long time, but the problem is that to reduce time, such a heuristic algorithm is needed that delivers a solution close to optimal which will be found quite fast. One of the possible solutions to this problem is the subject of this article.
      The subject of the research in this article is the choice of the best heuristic algorithm which, when applied, leads to an increase in temporal efficiency in combination with the algorithm of the branch and bound method, and an experimental study of its software implementation in order to obtain an average time for solving individual problems. On the basis of the results obtained, recommendations are given on the limiting dimensions of the problem that allow for an acceptable solution time, something which is of interest in the practical application of this combined algorithm in the tasks of business informatics and logistics.

      In this paper we describe an easy-to-implement algorithm for automatedgeneration of the linguistic variable term membership functions to allow for information search in a relational database based on qualitative criteria by means of the SQL query language.
      The proposed algorithm makes it possible to calculate the parameters of the triangular and trapezoid membership functions taking into account the distribution of the variable of interest stored in the database. The algorithm defines the intervals covered by the term bases, so that each interval contains about the same number of values. Upper bounds of the defined intervals are used to calculate the parameters of membership functions. The parameters of the membership functions generated with this algorithm can be easily calculated with the limited computational means of the SQL language.
      We review the algorithm realizations for the generation of 3 and 5 terms of a linguistic variable based on a sample from a database containing 100 or 500 different values.
      The membership functions obtained through the algorithm have the required properties of orderliness, completeness, consistency and normality. They do not require further approximation. Unlike the known methods, the algorithm does not require significant computing resources, the use of specialized software, settings configuring, or a training set formation.
      The algorithm implementation creates opportunities to support fuzzy search queries in relational databases using the means of the SQL language, as limited as they are. Thus, the system’s level of intelligence would be increased, and the user would be provided with the means of search query formulation in a natural language. The linguistic variable terms generated using our algorithm can be used within the framework of a fuzzy rule-based knowledge base of an information system, as well as to perform fuzzy inference.

      Knowledge management (KM) is a practice where knowledge is captured, distributed and utilized effectively, leading to enhanced productivity and performance of an organization. The prime objective of this study is to examine the influence of KM processes and capabilities on the performance of small and medium-sized enterprises (SMEs) in Saudi Arabia. KM capabilities comprise people, IT, the organizational structure and the organizational culture, which are measured in this research by T-shaped skills, IT support, the level of centralization, and learning. The other dimension is KM processes, which consist of accessing, generating, embedding, representing, facilitating, using, measuring and transferring knowledge. Moreover, KM performance is measured via two factors: the organization’s financial performance and customer satisfaction.
      The research reviews previous literature related to the KM components (processes, capabilities and performance) to develop the research model and a number of hypotheses to evaluate the research problem. The data is collected through a questionnaire-based survey completed by a total of 126 managers working in different sectors of Saudi SMEs. With the help of a number of statistical tests, the research study found that that the KM capabilities, IT support, learning culture, decentralized structure and the people of the organization contribute to the success of KM practices or processes, validating the theoretical model. The results also show that KM processes, including accessing, generating, measuring, transferring, use, embedding, representing and facilitating, are positively associated with the performance of SMEs in Saudi Arabia.

      The introduction of the institution of cadastral value in the Russian Federation opens up new opportunities in real estate valuation. In this regard, the new focus for appraisers is statistical analysis of multidimensional empirical distributions that were not previously available, because the real estate market does not have pairwise and multidimensional observations concentrated in unified databases. Data of interest to analysts is usually concentrated in different sources from different owners and pertains to different objects. The goal of combining them can be solved by comparing such data with the data of cadastral records, namely the cadastral number as a unique identifier of the object. Since the cadastral value corresponds to each cadastral number, it is possible to compare the cadastral value with important indicators such as the market price of the offer, the transaction price, the rental rate, the annual price indices, the capitalization rate, the discount rate, the trading discount and many other indicators, the formation of which involves more than two random variables. The construction of the model involves the principle of following the prices formed by pair comparisons to geometric Brownian motion, and hence the formation of lognormal population. As it turned out, as a result of large-scale cadastral work carried out in the Russian Federation in 2014, the cadastral value is also subject to lognormal distribution of prices (in each class of objects). For the market value (as the most probable price of the transaction under conditions of perfect competition), this leads to functional dependences from the cadastral value of the power type. Similarly, many other indicators will also be subject to dependences in the form of power functions. Obviously, having a function depending from the various indicators of cadastral value across the set of values, you can set the relationship between the various indicators, which was impossible before the introduction of the institution of cadastral value. This article proposes a method of calculating the trading discount when appraising real estate based on analysis of market statistics and databases of cadastral records. An analytical formula of the dependence of trading discounts from the offer price is proposed. The method allows us to set the level of the discount not only for objects included in an advertising database, but also for any object that has undergone cadastral registration.

      This study presents the analysis of one of the major contemporary transformational forces – the Internet of Things (IoT), which significantly influences the future development of all spheres of life. The purpose of the research is to identify the potential economic effects of IoT implementation in different markets. To achieve this goal, the following tasks are consistently solved in the study: identification and classification of the main IoT applications markets; detection, assessment and analysis of the economic effects of the IoT in the selected segmentswithin the proposed classification; formation of future directions of IoT development. Based on the combination of such methodological approaches as technology life cycle and technology adoption life cycle, perspectives of the IoT development are set out.The technology life cycle is viewed through the prism of the methodology of the research company Gartner (the Gartner Hype Cycle for Emerging Technologies), based on establishing a consensus among a wide range of assessments of leading experts in the field of information and communication technologies. Comparison of the two methods and expert assessments allows us to conclude that, according to the methodology of technology adoption life cycle, the Internet of Things is of interest only for a group of “early adopters.”