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One approach to solving integer linear programming problems is to ignore the integer constraint and solve the problem with continuous decision variables. This is referred to as:Group of answer choicesQuick solution methodLP satisfyingLP relaxationLP approximation

Question

One approach to solving integer linear programming problems is to ignore the integer constraint and solve the problem with continuous decision variables. This is referred to as:Group of answer choicesQuick solution methodLP satisfyingLP relaxationLP approximation

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Solution

The correct answer is "LP relaxation."

Explanation:

In the context of integer programming, "LP relaxation" refers to the process of ignoring the integer constraints and solving the problem as a linear programming problem with continuous decision variables. This approach can provide a good starting point or an upper or lower bound for the optimal solution of the integer programming problem. However, the solution obtained from LP relaxation may not be feasible or

This problem has been solved

Similar Questions

A feasible solution to an integer programming problem is ensured by rounding down non-integer solution values.Group of answer choicesTrueFalse

What kind of solution do you obtain when you solve a relaxation of an integer optimization problem?Always an integer solutionA solution without considering integer constraintsA solution without any constraintsAlways a zero-one solution

The first step in a branch and bound approach to solving integer programming problems is toans.graph the problem.change the objective function coefficients to whole integer numbers.none of the abovesolve the original problem using LP by allowing continuous non integer solutions. Previous Marked for Review Next

What type of problem involves both integer and linear decision variables?Mixed-integer linear programming (MILP)Quadratic programmingNonlinear integer programmingDual programming

Solving an integer programming problem by rounding off answers obtained by solving it as a linear programming problem (using Simplex LP), we find thatGroup of answer choicesThe values of decision variables obtained by rounding off are always very close to the optimal values.The value of the objective function for a maximization problem will likely be less than that for the Simplex LP solution.The value of the objective function for a minimization problem will likely be less than that for the Simplex LP solution.All constraints are satisfied exactly.

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