Burgess Final - Multiple Choice

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False

A "balanced problem" exists in a transportation model when the optimal solution has the same amount being shipped over all paths that have any positive shipment

True

A common objective is cost minimization

False

Any time that we have an isoprofit line that is parallel to a constraint, we always will have alternative optimal solutions

False

Both transportation and assignment models involve the distribution of goods from sources to destinations

Minimal spanning tree

If your goal was to construct a network in which all points were connected and the distance between them was as short as possible, the technique that you would use is

True

In an assignment problem the number of rows and columns must be equal

False

In linear programming terminology, "shadow price" and "reduced cost" are synonyms

False

In sensitivity analysis, we can calculate the effects on the objective function of changing more than one of the coefficients at the same time

False

In some instances, an unbounded problem may be the optimum found by the corner point method

Shortest route

Kind of problems that can be solved as a linear program using binary decision variables

MILP

Modified type of integer programming

AILP

Plain type of integer programming

True

The assignment problem can have a maximization objective

True

The constraint X1 + X2 ≤ 1 with 0 -1 integer programming allows for either X1 or X2 to be a part of the optimal solution, but not both

Pick any path with some flow

The first step in the maximal-flow technique is to

Shadow Price

The increase in the objective function value that results from a one-unit increase in the right-hand side of that constraint is called the

True

The number of units shipped into and out of transshipment points should be equal (transshipment problem)

source

The origin or beginning node in a network is called

True

The set of solution points that satisfies all of a linear programming problem's constraints simultaneously is defined as the feasible region in graphical linear programming

True

The transportation, transshipment, and assignment problems can all be solved using linear programming

True

The transshipment problem is a special class of transportation problems

True

There can be constraints on the number of units shipped into a destination point (transshipment problem)

True

There can be constraints on the number of units shipped out of an origin point (transshipment problem)

False

Utilization of Bayes' theorem requires the use of expected monetary values (EMV)

True

When solving very large integer programming problems, we sometimes have to settle for a "good," not necessarily optimal, answer

True

When two or more constraints conflict with one another, we have a condition called infeasibility

BILP

Zero-one type of integer programming

risk certainty uncertainty

three decision-making environments are decision making under


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