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In linear programming problems the optimum solution
- a)satisfies a set of piecewise – linear inequalities (called constraints)
- b)satisfies a set of linear inequalities (called linear constraints)
- c)satisfies a set of quadratic inequalities (calledconstraints)
- d)satisfies a set of cubic inequalities (calledconstraints)
Correct answer is option 'B'. Can you explain this answer?
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In linear programming problems the optimum solutiona)satisfies a set o...
In linear programming problems the optimum solution satisfies a set of linear inequalities (called linear constraints) .
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In linear programming problems the optimum solutiona)satisfies a set o...
Explanation:
Linear Programming Problems:
Linear programming involves optimizing a linear objective function subject to a set of linear constraints. The goal is to find the values of the decision variables that maximize or minimize the objective function while satisfying all constraints.
Optimum Solution:
The optimum solution in linear programming problems refers to the values of the decision variables that result in the maximum or minimum value of the objective function while still meeting all the constraints.
Linear Inequalities:
In linear programming, the constraints are typically represented as linear inequalities. These are mathematical statements that involve linear expressions (variables raised to the power of 1) connected by inequality symbols such as ≤, ≥, or =.
Optimum Solution and Linear Inequalities:
The optimum solution in linear programming satisfies a set of linear inequalities, also known as linear constraints. These constraints define the feasible region within which the optimal solution must lie. The optimal solution is the point within this feasible region that maximizes or minimizes the objective function.
Conclusion:
Therefore, in linear programming problems, the optimum solution always satisfies a set of linear inequalities or linear constraints. This is a fundamental aspect of linear programming and is crucial for finding the most efficient solutions to optimization problems.
Linear Programming Problems:
Linear programming involves optimizing a linear objective function subject to a set of linear constraints. The goal is to find the values of the decision variables that maximize or minimize the objective function while satisfying all constraints.
Optimum Solution:
The optimum solution in linear programming problems refers to the values of the decision variables that result in the maximum or minimum value of the objective function while still meeting all the constraints.
Linear Inequalities:
In linear programming, the constraints are typically represented as linear inequalities. These are mathematical statements that involve linear expressions (variables raised to the power of 1) connected by inequality symbols such as ≤, ≥, or =.
Optimum Solution and Linear Inequalities:
The optimum solution in linear programming satisfies a set of linear inequalities, also known as linear constraints. These constraints define the feasible region within which the optimal solution must lie. The optimal solution is the point within this feasible region that maximizes or minimizes the objective function.
Conclusion:
Therefore, in linear programming problems, the optimum solution always satisfies a set of linear inequalities or linear constraints. This is a fundamental aspect of linear programming and is crucial for finding the most efficient solutions to optimization problems.
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In linear programming problems the optimum solutiona)satisfies a set of piecewise – linear inequalities (called constraints)b)satisfies a set of linear inequalities (called linear constraints)c)satisfies a set of quadratic inequalities (calledconstraints)d)satisfies a set of cubic inequalities (calledconstraints)Correct answer is option 'B'. Can you explain this answer?
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In linear programming problems the optimum solutiona)satisfies a set of piecewise – linear inequalities (called constraints)b)satisfies a set of linear inequalities (called linear constraints)c)satisfies a set of quadratic inequalities (calledconstraints)d)satisfies a set of cubic inequalities (calledconstraints)Correct answer is option 'B'. Can you explain this answer? for JEE 2024 is part of JEE preparation. The Question and answers have been prepared according to the JEE exam syllabus. Information about In linear programming problems the optimum solutiona)satisfies a set of piecewise – linear inequalities (called constraints)b)satisfies a set of linear inequalities (called linear constraints)c)satisfies a set of quadratic inequalities (calledconstraints)d)satisfies a set of cubic inequalities (calledconstraints)Correct answer is option 'B'. Can you explain this answer? covers all topics & solutions for JEE 2024 Exam. Find important definitions, questions, meanings, examples, exercises and tests below for In linear programming problems the optimum solutiona)satisfies a set of piecewise – linear inequalities (called constraints)b)satisfies a set of linear inequalities (called linear constraints)c)satisfies a set of quadratic inequalities (calledconstraints)d)satisfies a set of cubic inequalities (calledconstraints)Correct answer is option 'B'. Can you explain this answer?.
In linear programming problems the optimum solutiona)satisfies a set of piecewise – linear inequalities (called constraints)b)satisfies a set of linear inequalities (called linear constraints)c)satisfies a set of quadratic inequalities (calledconstraints)d)satisfies a set of cubic inequalities (calledconstraints)Correct answer is option 'B'. Can you explain this answer? for JEE 2024 is part of JEE preparation. The Question and answers have been prepared according to the JEE exam syllabus. Information about In linear programming problems the optimum solutiona)satisfies a set of piecewise – linear inequalities (called constraints)b)satisfies a set of linear inequalities (called linear constraints)c)satisfies a set of quadratic inequalities (calledconstraints)d)satisfies a set of cubic inequalities (calledconstraints)Correct answer is option 'B'. Can you explain this answer? covers all topics & solutions for JEE 2024 Exam. Find important definitions, questions, meanings, examples, exercises and tests below for In linear programming problems the optimum solutiona)satisfies a set of piecewise – linear inequalities (called constraints)b)satisfies a set of linear inequalities (called linear constraints)c)satisfies a set of quadratic inequalities (calledconstraints)d)satisfies a set of cubic inequalities (calledconstraints)Correct answer is option 'B'. Can you explain this answer?.
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