FAST ALGORITHM FOR SOLVING A ONE-DIMENSIONAL UNCLOSED DESIRABLE NEIGHBORS PROBLEM

Abstract

Contex. The paper formulates a general combinatorial problem for the desired neighbors. Possible areas of practical application of the results of its development are listed. Within the framework of this problem, an analysis of the scientific literature on the optimization of combinatorial problems of practical importance that are close in subject is carried out, on the basis of which the novelty of the formulated problem accepted for scientific and algorithmic development is established. Objective. For a particular case of the problem, the article formulates a one-dimensional unclosed integer combinatorial problem of practical importance about the desired neighbors on the example of the problem of distributing buyers on land plots, taking into account their recommendations on the desired neighborhood. Method. A method for solving the mentioned problem has been developed and an appropriate effective algorithm has been created, which for thousands of experimental sets of hundreds of distribution subjects allows to get the optimal result on an ordinary personal computer in less than a second of counting time. The idea of developing the optimization process is expressed, which doubles the practical effect of optimization by cutting off unwanted neighbors without worsening the maximum value of the desirability criterion. Results. The results of the work include the formulation of a one-dimensional unclosed combinatorial problem about the desired neighbors and an effective algorithm for its solution, which makes it possible to find one, several, and, if necessary, all the options for optimal distributions. The main results of the work can also include the concept and formulation of a general optimization combinatorial problem of desirable neighbors, which may have theoretical and practical prospects. Conclusions. The method underlying the algorithm for solving the problem allows, if necessary, to easily find all the best placement options, the number of which, as a rule, is very large. It is established that their number can be reduced with benefit up to one by reducing the number of undesirable neighborhoods, which contributes to improving the quality of filtered optimal distributions in accordance with this criterion. The considered problem can receive prospects for evolution and development in various subject areas of the economy, production, architecture, urban studies and other spheres.