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The problem of solving the task of discrete optimization is not completely solved. Lack of publications, scientific developments, algorithms and software products do not give the ability to transfer the mathematical apparatus of solving discrete optimization problems to the class P of computational complexity. All analytical and combinatorial algorithms for solving problems of linear and non-linear optimization are NP completeness. There are developments to improve the efficiency of robotic algorithms, they are filled with requests and actual ones. In this paper, it is proposed to use deterministic and probabilistic methods for forming a priority queue of decision vector components in order to assign positive values to them. After the formation of the variant of the solution, it is possible to vectorize as if the approached solution is taken away from the record value of the goal function, which in exact algorithms is like a solution, which results in a polyp. In this paper has a method for forming a priority line for concretizing the components of the solution vector. The basis of deterministic methods is the idea of a greedy algorithm. The location in the queue is determined by the value of the corresponding component of the cost vector. The appearance of the value of non-visibility in the system of restrictions increases the priority of the component. Behind such a way, another method of determination is modified. Probability assessment probability of priorities is based on the ideas of algorithms in an ant colony and simulated annealing. The scope of probability indicates the significance of the component - a contender for a positive value. A numerical example of a small variability of the task about a knapsack has been introduced, which demonstrates the imitation of a nearby solution. [ABSTRACT FROM AUTHOR]

Copyright of National Academy of Sciences of Armenia Reports / Doklady Nacionalnaâ Akademiâ Nauk Armenii is the property of National Academy of Sciences of the Republic of Armenia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The task of path finding by an agent is one of the basic tasks and is of great practical importance. As a rule, this is an optimization task that is solved in the space of the state graph in order to minimize the length of the path. Such a task becomes more difficult and becomes even more popular if it is solved on the basis of one graph space by several agents. In this case, another practically important optimization parameter appears, which is expressed by the number of conflicts between agents. Such an abstract formulation of the task has numerous variants of formalization and a large number of approaches to its solution. In this paper, the main element of the approach is the application of the classic Dijkstra algorithm, which is executed sequentially by each agent. When finding the shortest route, each agent modifies the graph space in such a way as to reduce the probability of conflicts with subsequent agents. This approach is original and a number of computational experiments were performed to verify it using software developed for this purpose. The experiments that were conducted demonstrate the adequate behavior of the main algorithm. The work analyzes the limitations inherent in the proposed approach within the framework of the abstract formulation of the task. The directions of further development of the basic approach have been determined. [ABSTRACT FROM AUTHOR]

Copyright of Foreign Language Teaching is the property of Az Buki National Publishing House and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Radio Electronics, Computer Science, Control is the property of Zaporizhzhia National Technical University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Geomatics & Information Science of Wuhan University is the property of Geomatics & Information Science of Wuhan University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì is the property of Odessa Polytechnic University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)