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What is a constraint in a linear programming problem? How is a constraint represented?

Short Answer

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In linear programming, a constraint is a condition that any solution to the problem must satisfy, often representing the limitations or requirements. Constraints are usually represented as linear inequalities that define feasible regions within a Cartesian plane.

Step by step solution

01

Understanding Constraints

In the context of linear programming, a constraint is a condition that the solution to an optimization problem must satisfy. It's the specific limitations or requirements that a problem's solutions need to meet. For example, if an optimization problem aims to maximize profit in a factory, constraints may set limits on the available resources, like raw materials or labour hours.
02

Representation of Constraints

Constraints in a linear programming problem are typically represented as linear inequalities. If the problem is represented in two dimensions (two variables), these inequalities define regions in a Cartesian plane; a point in this region satisfies all constraints and is a feasible solution to the problem. For instance, if labor hours can't exceed a certain number, it may be represented as a constraint like \( x \leq 40 \), where x is the number of labour hours.

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Most popular questions from this chapter

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