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Along with the traditional material concerning linear programming
(the simplex method, the theory of duality, the dual simplex
method), In-Depth Analysis of Linear Programming contains new
results of research carried out by the authors. For the first time,
the criteria of stability (in the geometrical and algebraic forms)
of the general linear programming problem are formulated and
proved. New regularization methods based on the idea of extension
of an admissible set are proposed for solving unstable (ill-posed)
linear programming problems. In contrast to the well-known
regularization methods, in the methods proposed in this book the
initial unstable problem is replaced by a new stable auxiliary
problem. This is also a linear programming problem, which can be
solved by standard finite methods. In addition, the authors
indicate the conditions imposed on the parameters of the auxiliary
problem which guarantee its stability, and this circumstance
advantageously distinguishes the regularization methods proposed in
this book from the existing methods. In these existing methods, the
stability of the auxiliary problem is usually only presupposed but
is not explicitly investigated. In this book, the traditional
material contained in the first three chapters is expounded in much
simpler terms than in the majority of books on linear programming,
which makes it accessible to beginners as well as those more
familiar with the area.
Along with the traditional material concerning linear programming
(the simplex method, the theory of duality, the dual simplex
method), In-Depth Analysis of Linear Programming contains new
results of research carried out by the authors. For the first time,
the criteria of stability (in the geometrical and algebraic forms)
of the general linear programming problem are formulated and
proved. New regularization methods based on the idea of extension
of an admissible set are proposed for solving unstable (ill-posed)
linear programming problems. In contrast to the well-known
regularization methods, in the methods proposed in this book the
initial unstable problem is replaced by a new stable auxiliary
problem. This is also a linear programming problem, which can be
solved by standard finite methods. In addition, the authors
indicate the conditions imposed on the parameters of the auxiliary
problem which guarantee its stability, and this circumstance
advantageously distinguishes the regularization methods proposed in
this book from the existing methods. In these existing methods, the
stability of the auxiliary problem is usually only presupposed but
is not explicitly investigated. In this book, the traditional
material contained in the first three chapters is expounded in much
simpler terms than in the majority of books on linear programming,
which makes it accessible to beginners as well as those more
familiar with the area.
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