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What are slack variables in LP?

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Slack variables are added to linear inequalities (constraints) to convert them into equalities. They represent unused resources in a maximization problem. 

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In linear programming (LP), slack variables are extra variables that are added to convert inequality constraints into equality constraints. To account for any resources that are left over or not utilized, they are employed in "less than or equal to" (≤) restrictions. The difference between the limit and the actual consumption is represented by the slack variable, for example, if a constraint states that a particular resource usage cannot exceed a limit. Because slack variables are always non-negative, they facilitate the use of simpler mathematical formulations when addressing LP problems through the use of techniques like the simplex algorithm. They support the viability of solutions rather than having a direct impact on the target function.

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Slack variables in linear programming (LP) are additional variables introduced to convert inequality constraints into equality constraints, allowing for the representation of unused resources or capacities within the constraints of the optimization problem.

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Slack variables are artificial variables introduced into linear programming (LP) problems to convert inequality constraints into equality constraints.

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Slack variables in linear programming are added to less-than-or-equal-to constraints to convert them into equalities. They represent the unused portion of resources and help in analyzing the feasibility of the solution.

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additional variables that are introduced into the linear constraints of a linear program to transform them from inequality constraints to equality constraints.

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