Operations Research interview questions

1. A.the convex set of all points satisfying every constraint, whose corner points are the only candidates for a linear optimum
2. B.a non-negative quantity added to a less-than-or-equal constraint to turn it into an equality for the simplex tableau
3. C.an optimisation of a linear objective function subject to linear equality and inequality constraints on non-negative decision variables
4. D.the time an activity can be delayed without delaying project completion, being zero for every activity on the critical path

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1. A.Programme evaluation and review technique
2. B.Crashing
3. C.Assignment problem
4. D.Linear programming problem

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1. A.Linear programming problem — the time an activity can be delayed without delaying project completion, being zero for every activity on the critical path
2. B.Linear programming problem — an optimisation of a linear objective function subject to linear equality and inequality constraints on non-negative decision variables
3. C.Linear programming problem — a probabilistic network method that derives each activity's expected duration from optimistic, most likely and pessimistic estimates using a beta-distribution weighting
4. D.Linear programming problem — a special transportation problem in which each of n jobs must be given to exactly one of n agents at minimum total cost

Answer + AI explanation with Pro

1. A.a distribution problem in which total supply equals total demand, so no dummy source or destination is needed before solving
2. B.the convex set of all points satisfying every constraint, whose corner points are the only candidates for a linear optimum
3. C.the row- and column-reduction algorithm that solves an assignment problem by creating enough zeros to cover all assignments with n lines
4. D.deliberately shortening activity durations at extra cost, applied to critical activities in order of least cost slope to compress the project

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1. A.Vogel's approximation method
2. B.Hungarian method
3. C.Assignment problem
4. D.Feasible region

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1. A.Feasible region — the convex set of all points satisfying every constraint, whose corner points are the only candidates for a linear optimum
2. B.Feasible region — an initial-solution rule for transportation problems that allocates along the row or column with the largest penalty between its two cheapest routes
3. C.Feasible region — a probabilistic network method that derives each activity's expected duration from optimistic, most likely and pessimistic estimates using a beta-distribution weighting
4. D.Feasible region — an optimisation of a linear objective function subject to linear equality and inequality constraints on non-negative decision variables

Answer + AI explanation with Pro

1. A.the row- and column-reduction algorithm that solves an assignment problem by creating enough zeros to cover all assignments with n lines
2. B.an iterative procedure that moves from one corner point of the feasible region to an adjacent better one until no improving direction remains
3. C.a special transportation problem in which each of n jobs must be given to exactly one of n agents at minimum total cost
4. D.the condition in which a basic variable takes the value zero, which can stall the simplex method by allowing iterations that do not improve the objective

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1. A.Total float of an activity
2. B.Assignment problem
3. C.Duality in linear programming
4. D.Simplex method

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1. A.Simplex method — an iterative procedure that moves from one corner point of the feasible region to an adjacent better one until no improving direction remains
2. B.Simplex method — a non-negative quantity added to a less-than-or-equal constraint to turn it into an equality for the simplex tableau
3. C.Simplex method — a distribution problem in which total supply equals total demand, so no dummy source or destination is needed before solving
4. D.Simplex method — an optimisation of a linear objective function subject to linear equality and inequality constraints on non-negative decision variables

Answer + AI explanation with Pro

1. A.the row- and column-reduction algorithm that solves an assignment problem by creating enough zeros to cover all assignments with n lines
2. B.a distribution problem in which total supply equals total demand, so no dummy source or destination is needed before solving
3. C.a non-negative quantity added to a less-than-or-equal constraint to turn it into an equality for the simplex tableau
4. D.deliberately shortening activity durations at extra cost, applied to critical activities in order of least cost slope to compress the project

Answer + AI explanation with Pro

1. A.Feasible region
2. B.Duality in linear programming
3. C.Total float of an activity
4. D.Slack variable

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1. A.Slack variable — a distribution problem in which total supply equals total demand, so no dummy source or destination is needed before solving
2. B.Slack variable — the correspondence by which every maximisation problem has an associated minimisation problem whose optimal objective value is identical
3. C.Slack variable — the row- and column-reduction algorithm that solves an assignment problem by creating enough zeros to cover all assignments with n lines
4. D.Slack variable — a non-negative quantity added to a less-than-or-equal constraint to turn it into an equality for the simplex tableau

Answer + AI explanation with Pro

1. A.an optimisation of a linear objective function subject to linear equality and inequality constraints on non-negative decision variables
2. B.a probabilistic network method that derives each activity's expected duration from optimistic, most likely and pessimistic estimates using a beta-distribution weighting
3. C.the correspondence by which every maximisation problem has an associated minimisation problem whose optimal objective value is identical
4. D.the condition in which a basic variable takes the value zero, which can stall the simplex method by allowing iterations that do not improve the objective

Answer + AI explanation with Pro

1. A.Crashing
2. B.Degeneracy in linear programming
3. C.Balanced transportation problem
4. D.Programme evaluation and review technique

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1. A.Degeneracy in linear programming — a special transportation problem in which each of n jobs must be given to exactly one of n agents at minimum total cost
2. B.Degeneracy in linear programming — the time an activity can be delayed without delaying project completion, being zero for every activity on the critical path
3. C.Degeneracy in linear programming — the condition in which a basic variable takes the value zero, which can stall the simplex method by allowing iterations that do not improve the objective
4. D.Degeneracy in linear programming — an iterative procedure that moves from one corner point of the feasible region to an adjacent better one until no improving direction remains

Answer + AI explanation with Pro

1. A.the row- and column-reduction algorithm that solves an assignment problem by creating enough zeros to cover all assignments with n lines
2. B.an initial-solution rule for transportation problems that allocates along the row or column with the largest penalty between its two cheapest routes
3. C.the convex set of all points satisfying every constraint, whose corner points are the only candidates for a linear optimum
4. D.the correspondence by which every maximisation problem has an associated minimisation problem whose optimal objective value is identical

Answer + AI explanation with Pro

1. A.Balanced transportation problem
2. B.Simplex method
3. C.Duality in linear programming
4. D.Assignment problem

Answer + AI explanation with Pro

1. A.Duality in linear programming — a non-negative quantity added to a less-than-or-equal constraint to turn it into an equality for the simplex tableau
2. B.Duality in linear programming — a distribution problem in which total supply equals total demand, so no dummy source or destination is needed before solving
3. C.Duality in linear programming — the row- and column-reduction algorithm that solves an assignment problem by creating enough zeros to cover all assignments with n lines
4. D.Duality in linear programming — the correspondence by which every maximisation problem has an associated minimisation problem whose optimal objective value is identical

Answer + AI explanation with Pro

1. A.a distribution problem in which total supply equals total demand, so no dummy source or destination is needed before solving
2. B.a non-negative quantity added to a less-than-or-equal constraint to turn it into an equality for the simplex tableau
3. C.the condition in which a basic variable takes the value zero, which can stall the simplex method by allowing iterations that do not improve the objective
4. D.the row- and column-reduction algorithm that solves an assignment problem by creating enough zeros to cover all assignments with n lines

Answer + AI explanation with Pro

1. A.Simplex method
2. B.Assignment problem
3. C.Balanced transportation problem
4. D.Hungarian method

Answer + AI explanation with Pro

1. A.Balanced transportation problem — the time an activity can be delayed without delaying project completion, being zero for every activity on the critical path
2. B.Balanced transportation problem — the condition in which a basic variable takes the value zero, which can stall the simplex method by allowing iterations that do not improve the objective
3. C.Balanced transportation problem — deliberately shortening activity durations at extra cost, applied to critical activities in order of least cost slope to compress the project
4. D.Balanced transportation problem — a distribution problem in which total supply equals total demand, so no dummy source or destination is needed before solving

Answer + AI explanation with Pro

1. A.an initial-solution rule for transportation problems that allocates along the row or column with the largest penalty between its two cheapest routes
2. B.the row- and column-reduction algorithm that solves an assignment problem by creating enough zeros to cover all assignments with n lines
3. C.an optimisation of a linear objective function subject to linear equality and inequality constraints on non-negative decision variables
4. D.the time an activity can be delayed without delaying project completion, being zero for every activity on the critical path

Answer + AI explanation with Pro

1. A.Simplex method
2. B.Assignment problem
3. C.Vogel's approximation method
4. D.Degeneracy in linear programming

Answer + AI explanation with Pro

1. A.Vogel's approximation method — the correspondence by which every maximisation problem has an associated minimisation problem whose optimal objective value is identical
2. B.Vogel's approximation method — the condition in which a basic variable takes the value zero, which can stall the simplex method by allowing iterations that do not improve the objective
3. C.Vogel's approximation method — a special transportation problem in which each of n jobs must be given to exactly one of n agents at minimum total cost
4. D.Vogel's approximation method — an initial-solution rule for transportation problems that allocates along the row or column with the largest penalty between its two cheapest routes

Answer + AI explanation with Pro

1. A.a special transportation problem in which each of n jobs must be given to exactly one of n agents at minimum total cost
2. B.the row- and column-reduction algorithm that solves an assignment problem by creating enough zeros to cover all assignments with n lines
3. C.a distribution problem in which total supply equals total demand, so no dummy source or destination is needed before solving
4. D.deliberately shortening activity durations at extra cost, applied to critical activities in order of least cost slope to compress the project

Answer + AI explanation with Pro

1. A.Assignment problem
2. B.Vogel's approximation method
3. C.Crashing
4. D.Slack variable

Answer + AI explanation with Pro

1. A.Assignment problem — the row- and column-reduction algorithm that solves an assignment problem by creating enough zeros to cover all assignments with n lines
2. B.Assignment problem — a special transportation problem in which each of n jobs must be given to exactly one of n agents at minimum total cost
3. C.Assignment problem — the correspondence by which every maximisation problem has an associated minimisation problem whose optimal objective value is identical
4. D.Assignment problem — a probabilistic network method that derives each activity's expected duration from optimistic, most likely and pessimistic estimates using a beta-distribution weighting

Answer + AI explanation with Pro

1. A.an initial-solution rule for transportation problems that allocates along the row or column with the largest penalty between its two cheapest routes
2. B.a special transportation problem in which each of n jobs must be given to exactly one of n agents at minimum total cost
3. C.the condition in which a basic variable takes the value zero, which can stall the simplex method by allowing iterations that do not improve the objective
4. D.the row- and column-reduction algorithm that solves an assignment problem by creating enough zeros to cover all assignments with n lines

Answer + AI explanation with Pro

1. A.Programme evaluation and review technique
2. B.Duality in linear programming
3. C.Crashing
4. D.Hungarian method

Answer + AI explanation with Pro

1. A.Hungarian method — the correspondence by which every maximisation problem has an associated minimisation problem whose optimal objective value is identical
2. B.Hungarian method — a probabilistic network method that derives each activity's expected duration from optimistic, most likely and pessimistic estimates using a beta-distribution weighting
3. C.Hungarian method — a distribution problem in which total supply equals total demand, so no dummy source or destination is needed before solving
4. D.Hungarian method — the row- and column-reduction algorithm that solves an assignment problem by creating enough zeros to cover all assignments with n lines

Answer + AI explanation with Pro