LP problem:

For solving a linear problem using simplex algorithm, first the linear problem is converted to its standard form.

Then a basic feasible solution is found which is easy if all the constraints are less than or equal with non-negative right hand side.

If all non basic variables have nonnegative coefficients in row 0 then that basic feasible solution is optimal.

If any variable have negative coefficient in row 0 then the variable with the most negative coefficient is chosen to enter the basis.

If one or more constraints have a negative right hand side then there is no longer a basic feasible solution.

A(1,0) and B(0,1) are the points since the constraint is of type less than or equal to.

Hence z is same at both A and B...

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Chapter 4.7, Problem 3P

Chapter 4.7, Problem 5P

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Chapter 4 Solutions

OPERATIONS RESEARCH >INTERNATIONAL EDITI

Ch. 4.1 - Prob. 1P Ch. 4.1 - Prob. 2P Ch. 4.1 - Prob. 3P Ch. 4.4 - Prob. 1P Ch. 4.4 - Prob. 2P Ch. 4.4 - Prob. 3P Ch. 4.4 - Prob. 4P Ch. 4.4 - Prob. 5P Ch. 4.4 - Prob. 6P Ch. 4.4 - Prob. 7P

Ch. 4.5 - Prob. 1P Ch. 4.5 - Prob. 2P Ch. 4.5 - Prob. 3P Ch. 4.5 - Prob. 4P Ch. 4.5 - Prob. 5P Ch. 4.5 - Prob. 6P Ch. 4.5 - Prob. 7P Ch. 4.6 - Prob. 1P Ch. 4.6 - Prob. 2P Ch. 4.6 - Prob. 3P Ch. 4.6 - Prob. 4P Ch. 4.7 - Prob. 1P Ch. 4.7 - Prob. 2P Ch. 4.7 - Prob. 3P Ch. 4.7 - Prob. 4P Ch. 4.7 - Prob. 5P Ch. 4.7 - Prob. 6P Ch. 4.7 - Prob. 7P Ch. 4.7 - Prob. 8P Ch. 4.7 - Prob. 9P Ch. 4.8 - Prob. 1P Ch. 4.8 - Prob. 2P Ch. 4.8 - Prob. 3P Ch. 4.8 - Prob. 4P Ch. 4.8 - Prob. 5P Ch. 4.8 - Prob. 6P Ch. 4.10 - Prob. 1P Ch. 4.10 - Prob. 2P Ch. 4.10 - Prob. 3P Ch. 4.10 - Prob. 4P Ch. 4.10 - Prob. 5P Ch. 4.11 - Prob. 1P Ch. 4.11 - Prob. 2P Ch. 4.11 - Prob. 3P Ch. 4.11 - Prob. 4P Ch. 4.11 - Prob. 5P Ch. 4.11 - Prob. 6P Ch. 4.12 - Prob. 1P Ch. 4.12 - Prob. 2P Ch. 4.12 - Prob. 3P Ch. 4.12 - Prob. 4P Ch. 4.12 - Prob. 5P Ch. 4.12 - Prob. 6P Ch. 4.13 - Prob. 2P Ch. 4.14 - Prob. 1P Ch. 4.14 - Prob. 2P Ch. 4.14 - Prob. 3P Ch. 4.14 - Prob. 4P Ch. 4.14 - Prob. 5P Ch. 4.14 - Prob. 6P Ch. 4.14 - Prob. 7P Ch. 4.16 - Prob. 1P Ch. 4.16 - Prob. 2P Ch. 4.16 - Prob. 3P Ch. 4.16 - Prob. 5P Ch. 4.16 - Prob. 7P Ch. 4.16 - Prob. 8P Ch. 4.16 - Prob. 9P Ch. 4.16 - Prob. 10P Ch. 4.16 - Prob. 11P Ch. 4.16 - Prob. 12P Ch. 4.16 - Prob. 13P Ch. 4.16 - Prob. 14P Ch. 4.17 - Prob. 1P Ch. 4.17 - Prob. 2P Ch. 4.17 - Prob. 3P Ch. 4.17 - Prob. 4P Ch. 4.17 - Prob. 5P Ch. 4.17 - Prob. 7P Ch. 4.17 - Prob. 8P Ch. 4 - Prob. 1RP Ch. 4 - Prob. 2RP Ch. 4 - Prob. 3RP Ch. 4 - Prob. 4RP Ch. 4 - Prob. 5RP Ch. 4 - Prob. 6RP Ch. 4 - Prob. 7RP Ch. 4 - Prob. 8RP Ch. 4 - Prob. 9RP Ch. 4 - Prob. 10RP Ch. 4 - Prob. 12RP Ch. 4 - Prob. 13RP Ch. 4 - Prob. 14RP Ch. 4 - Prob. 16RP Ch. 4 - Prob. 17RP Ch. 4 - Prob. 18RP Ch. 4 - Prob. 19RP Ch. 4 - Prob. 20RP Ch. 4 - Prob. 21RP Ch. 4 - Prob. 22RP Ch. 4 - Prob. 23RP Ch. 4 - Prob. 24RP Ch. 4 - Prob. 26RP Ch. 4 - Prob. 27RP Ch. 4 - Prob. 28RP

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Solution Summary: The author explains the basic feasible solution of a linear problem using simplex algorithm, which is easy if all the constraints are less than or equal with non-negative right hand side.

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