Open AccessDirect Method for Solving Bilinear Programming Problem
Author(s) -
Л. Д. Матвеева
Publication year - 2021
Publication title -
nauka i tehnika
Language(s) - English
Resource type - Journals
eISSN - 2414-0392
pISSN - 2227-1031
DOI - 10.21122/2227-1031-2021-20-2-179-184
Subject(s) - mathematical optimization , bilinear interpolation , mathematics , linear programming , optimization problem , function (biology) , set (abstract data type) , plan (archaeology) , convex optimization , dual (grammatical number) , decomposition method (queueing theory) , computer science , regular polygon , history , art , statistics , geometry , literature , archaeology , evolutionary biology , biology , programming language , discrete mathematics
The bilinear programming problem is considered, where a column, which corresponds to one of the variables, is not fixed but can be chosen from a convex set. This problem is known as the Dantzig – Wolfe problem. Earlier, a modified support method was proposed to solve the problem, using the decomposition of the problem constraints of the Dantzig – Wolfe method. The author of the paper has developed a direct exact method for solving the formulated problem. The method is based on the idea of the solving a linear programming problem with generalized direct constraints and a general concept of an adaptive solution method. The notions of support, support plan, optimal and suboptimal (e-optimal) plan are introduced which is a given approximation of the objective function to the optimal plan of the problem. Criteria for optimality and suboptimality of the support plan have been formulated and have been proved in the paper. The search for the optimal solution is based on the idea of maximizing the increment of the objective function. This approach allows more fully to take into account the main target and structure of the problem. Improving a support plan consists of two parts: replacing the plan and replacing the support. To find a suitable direction, a special derived problem is solved while taking into account the main constraints of the problem. The replacement of the support is based on the search for the optimal plan of the dual problem. The method leads to an optimal solution to the problem in a finite number of iterations (in the case of a non-degenerate value).