Consider the application of the simplex method to an LP of standard form. Assume that the rows of the matrix A are linearly independent. Give either a proof or a counterexample to the following statements. a. An iteration of the simplex method may move the feasible solution by a positive distance while leaving the cost unchanged b. A variable that has just left the basis can not reenter in the very next iteration c. A variable that has just entered the basis can not leave in the very next iteration

Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter2: Systems Of Linear Equations
Section2.2: Direct Methods For Solving Linear Systems
Problem 3BEXP
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Consider the application of the simplex method to an LP of standard form. Assume that the rows of the
matrix A are linearly independent. Give either a proof or a counterexample to the following statements.
a. An iteration of the simplex method may move the feasible solution by a positive distance while
leaving the cost unchanged
b. A variable that has just left the basis can not reenter in the very next iteration
c. A variable that has just entered the basis can not leave in the very next iteration
d. If there is a non degenerate optimal basis, then there exists a unique optimal basis
e. If x is an optimal solution, no more than m of its components can be positive, where m is the number
of equality constraints.
Transcribed Image Text:Consider the application of the simplex method to an LP of standard form. Assume that the rows of the matrix A are linearly independent. Give either a proof or a counterexample to the following statements. a. An iteration of the simplex method may move the feasible solution by a positive distance while leaving the cost unchanged b. A variable that has just left the basis can not reenter in the very next iteration c. A variable that has just entered the basis can not leave in the very next iteration d. If there is a non degenerate optimal basis, then there exists a unique optimal basis e. If x is an optimal solution, no more than m of its components can be positive, where m is the number of equality constraints.
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