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Linear programming can be used to solve problems requiring the optimisation (maximum or minimum) of a linear objective function when the variables are subject to a linear constraints.

Q: What are the scope of linear programming?

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1. What do you understand by Linear Programming Problem? What are the requirements of Linear Programming Problem? What are the basic assumptions of Linear Programming Problem?

necessity of linear programming on organization.

the significance of duality theory of linear programming

essential attributes of linear programming models and its uses

A linear objective function and linear constraints.

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1. What do you understand by Linear Programming Problem? What are the requirements of Linear Programming Problem? What are the basic assumptions of Linear Programming Problem?

1. What do you understand by Linear Programming Problem? What are the requirements of Linear Programming Problem? What are the basic assumptions of Linear Programming Problem?

necessity of linear programming on organization.

the significance of duality theory of linear programming

essential attributes of linear programming models and its uses

Integer programming is a method of mathematical programming that restricts some or all of the variables to integers. A subset of Integer programming is Linear programming. This is a form of mathematical programming which seeks to find the best outcome in such a way that the requirements are linear relationships.

A linear objective function and linear constraints.

Toshinori Munakata has written: 'Matrices and linear programming with applications' -- subject(s): Linear programming, Matrices 'Solutions manual for Matrices and linear programming'

Howard Karloff has written: 'Linear programming' -- subject(s): Linear programming

Integer programming is a subset of linear programming where the feasible region is reduced to only the integer values that lie within it.

A linear objective function and linear constraints.

Linear Programming is used for determining a way to find the best solution or outcome for a given mathematical model represented as a linear relationship.