Question:
In a linear programming problem ,the restrictions under which the objective function is to be optimized are called as?
In a linear programming problem ,the restrictions under which the objective function is to be optimized are called as?
Updated On: Jun 7, 2024
decision variables
Objective function
constraints
Integer solution
optimal solutions
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The Correct Option is C
Solution and Explanation
In a linear programming problem, the constraints under which the objective function is to be optimized are called "constraints".
Let's deep dive into few interesting informations
- Constraints are mathematical expressions or inequalities that limit the possible domain of the objective function.
- They represent constraints or constraints imposed on the decision variables of a problem.
- The goal of linear programming is to find the values of the decision variables that satisfy all constraints in the optimization (maximization or minimization) of the objective function.
- The feasible region is the set of all possible solutions that satisfy the constraints, and the optimal solution is the point within the feasible region that maximizes or minimizes the objective function.
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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.