In a linear programming problem ,the restrictions under which the objective function is to be optimized are called as?
decision variables
Objective function
constraints
Integer solution
optimal solutions
The Correct Option is C
Approach Solution - 1
In a linear programming problem, the restrictions under which the objective function is to be optimized are called constraints.
The key components are:
- Decision variables (A): The variables that represent quantities to be determined
- Objective function (B): The function to be maximized or minimized
- Constraints (C): The restrictions or limitations on the decision variables
Since the question specifically asks about the restrictions, the correct answer is (C) constraints.
Approach Solution -2
In a linear programming problem, the restrictions under which the objective function is to be optimized are called constraints.
Some important components of linear programming are:
- Constraints (C): The restrictions or limitations on the decision variables
- Objective function (B): The function to be maximized or minimized
- Decision variables (A): The variables that represent quantities to be determined
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Concepts Used:
Linear Programming
Linear programming is a mathematical technique for increasing the efficiency and effectiveness of operations under specific constraints. The main determination of linear programming is to optimize or minimize a numerical value. It is built of linear functions with linear equations or inequalities restricting variables.
Characteristics of Linear Programming:
- Decision Variables: This is the first step that will determine the output. It provides the final solution to the problem.
- Constraints: The mathematical form in which drawbacks are expressed, regarding the resource.
- Data: They are placeholders for known numbers to make writing complex models simple. They are constituted by upper-case letters.
- Objective Functions: Mathematically, the objective function should be quantitatively defined.
- Linearity: The function's relation between two or more variables must be straight. It indicates that the variable's degree is one.
- Finiteness: Input and output numbers must be finite and infinite. The best solution is not possible if the function consists infinite components.
- Non-negativity: The value of the variable should be either positive (+ve) or 0. It can't be a negative (-ve) number.