One.
To be a (non-trivial) linear programming problem both the objective function and the constraints must be linear.
If there were no constraints then the objective function could be made arbitrarily large or arbitrarily small. (Think of a line in two-space.)
By adding one constraint the objective function's value can be limited to a finite value.
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.
There is no limit.
It is a programming problem in which the objective function is to be optimised subject to a set of constraints. At least one of the constraints or the objective functions must be non-linear in at least one of the variables.
A linear objective function and linear constraints.
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?
Infeasibility occurs in a linear programming problem when there is no solution that satisfies all the constraints simultaneously.
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.
There is no limit.
It is a programming problem in which the objective function is to be optimised subject to a set of constraints. At least one of the constraints or the objective functions must be non-linear in at least one of the variables.
In linear programming, infeasibility refers to a situation where no feasible solution exists for a given set of constraints and objective function. This can occur when the constraints are contradictory or when the feasible region is empty. Infeasibility can be detected by solving the linear programming problem and finding that no solution satisfies all the constraints simultaneously. In such cases, the linear programming problem is said to be infeasible.
a mainframe computer is required
A linear objective function and linear constraints.
A linear objective function and linear constraints.
It is usually the answer in linear programming. The objective of linear programming is to find the optimum solution (maximum or minimum) of an objective function under a number of linear constraints. The constraints should generate a feasible region: a region in which all the constraints are satisfied. The optimal feasible solution is a solution that lies in this region and also optimises the obective function.
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?
The objective function and the constraints.