The article deals with the placement of service facilities and infrastructure. The most typical statements of problems are given. It is shown that the greatest difficulty is the simultaneous consideration of budget constraints and restrictions on the relative location of objects. It is shown that the application of the method of dynamic programming, in many ways can solve these problems. A heuristic algorithm for solving the problem is proposed. The issue of determining the rational number of objects intended for placement is considered. In this case, the problem reduces to determining the matching of maximum power. A heuristic algorithm is proposed that allows you to determine the required number of objects to be placed.
A model for the selection of options for the production of work in a construction project is considered, when each option is characterized by a set of criteria. The number of analyzed options is being reduced based on the construction of the Pareto-optimal solution set. The remaining options are used to solve the problem based on the network model,\ in which the solution will be a subcritical path that meets budgetary constraints. At the same time, the proposed comprehensive indicator characterizing the preferences of the customer makes it possible to determine alternative options for performing work in the energy project in such a way that the amount of costs allocated to implement the set of work under consideration is minimal. Another statement of the problem is also considered when it is necessary to determine a strategy for the implementation of an energy project that, given a planned budget constraint, maximizes the growth of a comprehensive indicator that characterizes customer preferences in this project. The solution of the tasks is given under the assumption of the convexity of the cost function.
We consider an arbitrary set of counterparties, united either in a social network or in the field of joint activities, for example, top management of an engineering company. It is required to build a rating for each participant based on the results of mutual evaluation of the participants of the association in question, when the significance of the counterparty’s assessment will depend on how it was evaluated by other participants in the association. To solve this problem, the interaction between counterparties was modeled in the form of a graph. For each vertex, its potential was determined, and for each edge of the graph, the flow along it. Based on these data, ratings were obtained from participants in the scientific and technical council of a machine-building enterprise. It is shown that using a similar algorithm, it is possible to obtain estimates of the significance of agents in social networks when conducting marketing research.
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