Штрафна функція максимуму в лінійному програмуванні
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
A linear program can be equivalently reformulated as an unconstrained nonsmooth minimization problem, whose objective is the sum of the original objective and a penalty function with a sufficiently large penalty parameter. The article presents two methods for choosing this parameter. The first one applies to linear programs with usual linear inequality constraints. Then, we use a corresponding theorem by N.Z. Shor on the equivalence of a convex program to an unconstrained nonsmooth minimization problem. The second method is for linear programs of a special type. This means that all inequalities are of the form that a linear expression on the left-hand side is less or equal to a positive constant on the right-hand side. For this special type, we use a corresponding theorem of B.N. Pshenichny on establishing a penalty parameter for convex programs. For differently sized linear programs of the special type, we demonstrate that suitable penalty parameters can be computed by a procedure in GNU Octave based on GLPK software.
Translated title of the contribution | Maximum Penalty Function in Linear Programming |
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Details
Original language | Ukrainian |
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Pages (from-to) | 156-160 |
Number of pages | 5 |
Journal | Physico-Mathematical Modelling and Informational Technologies |
Issue number | 33 |
Publication status | Published - 2021 |
Peer-reviewed | Yes |
External IDs
Mendeley | e386098e-20a7-3f3e-9c55-232c27a47976 |
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unpaywall | 10.15407/fmmit2021.33.156 |