Substantiation of clusterization of criterial space in linear programming problems
DOI:
https://doi.org/10.15587/1729-4061.2013.9172Keywords:
clusterization, criterial space, multicriteria, linear programming.Abstract
The article is devoted to the substantiation of appropriateness and benefits of using of clusterization of criterial space to improve the efficiency of solution of vector problems of linear programming with criterial space of large dimension. The examples of two multicriteria problems of linear programming showed that the clusterization of criterial space for their solution in comparison with the usual method of additive convolution permitted to ”manipulate” the necessary degree of ”compromise” of the found optimal solution and provided an opportunity to resolve the issue of compensation of one group of criteria for the account of others, using conventional additive convolution. Clusterization of criterial space on sets of strongly bound criteria permits to explore the relationship between the criteria of efficiency, which in turn allows more precise selection of weight coefficients.References
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