Burgess Final - Multiple Choice
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
