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No. 1a and 3d are linear, but 2bc is not. ■

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Q: Is Z equals 1A plus 2BC plus 3D a linear programming objective function?
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Related questions

What are the components of linear programming?

A linear objective function and linear constraints.


What are the components of programming?

A linear objective function and linear constraints.


What are the components of linear programming models?

The objective function and the constraints.


What are the scope of linear programming?

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.


What is non linear programming problem?

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.


What is a summary of linear programming?

It is a process by which a linear function of several variables, called the objective function, is maximised or minimised when it is subject to one or more linear constraints in the same variables.


Difference between function and objective function?

The linear function Z=c1x1+c2x2+c3x3+..........+cnxn which is to minimized or maximized is called Objective Function of general Linear Programming Problem.The innequalities of LPP are called constraints.


Can a linear programming problem have multiple solutions?

Yes. If the feasible region has a [constraint] line that is parallel to the objective function.


Can you use differential equations in linear programming?

I'm not altogether clear about what you mean. However, the term 'linear programming' means a category of optimisation problems in which both the objective function and the constraints are linear. Please see the link.


What is optimal feasible solution?

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.


What is the minimum number of constraints a linear programming problem can have?

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.


What are the Applications in linear program?

The applications are in finding optimum solutions to a linear objective function, subject to a number of linear constraints.