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CHAPTER 14: Optimization Modeling: Applications Glossary Terms: pg. 409 MULTIPLE CHOICE
- Which of the following does not represent a broad class of applications of linear programming models? pg. 328 (^) a.Blending models -used to find optimal combo of outputs & mix of inputs to produce desired results. pg. 398 pg. (^361) b. Financial portfolio models-used to determine the % of assets to invest in stocks, gold, & treasury bills. pg. 334 c.Logistics models-used to find MIN-Cost shipping method for satisfying customer demands. pg. 387 d. Set covering models e. Forecasting models ANS: E PTS: 1 MSC: AACSB: Analytic
- Many organizations must determine how to schedule employees to provide adequate service. If we assume that an organization faces the same situation each week, this is referred to as a. static scheduling problem- company faces same situation each week (pg. 327). b. dynamic scheduling problem-company does not face same situation each week (pg.
c. transportation scheduling problem
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d. All of these options ANS: A PTS: 1 MSC: AACSB: Analytic
- Workforce scheduling problems are often integer programming models, which means that they have: (pg. 321) a. an integer objective function b. integer decision variables (pg. 325) c. integer constraints d. all of these options ANS: C PTS: 1 MSC: AACSB: Analytic
- A common characteristic of integer programming models is that they: a. are easy to solve graphically (pg. 372) b. produce the same answer and standard linear programming models c. often produce multiple optimal solutions d. all of these options ANS: C PTS: 1 MSC: AACSB: Analytic
- Which of the following is true regarding multiple optimal solutions? a. All solutions have the same values for the decision variables b. All solutions have the same value for the objective function c. All solutions have the same shadow prices d. All of these options
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ANS: A PTS: 1 MSC: AACSB: Analytic
- Rounding the solution of a linear programming to the nearest integer values provides a(n) a. integer solution that is optimal b. integer solution that may be neither feasible nor optimal c. feasible solution that is not necessarily optimal d. infeasible solution ANS: B PTS: 1 MSC: AACSB: Analytic (pg. 378)
- Which of the following statements are false? (pg. 326) (^) a. Solver does not offer a sensitivity report for models with integer constraints (pg. 327) b. Solver’s sensitivity report is not suited for questions about multiple input changes (pg. 327) c. Solver’s sensitivity report is used primarily for questions about one-at-a time changes to input d. None of these options ANS: D PTS: 1 MSC: AACSB: Analytic
- If refers to the number of hours employee works in week , then to indicate that the number of working hours of 4 employees in week 3 should not exceed 160 hours, we must have a constraint of the form a. b. c. d. (^) X= # hours i= employee j=week
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Xij = # of hrs, employee "i" works in week "j" Prob 09: 4 employ 3rd week <= 160 hrs ANS: B PTS: 1 MSC: AACSB: Analytic
- Which of the following statements is a type of constraint that is often required in blending problems? a. Integer constraint b. Binary constraint (pg. 329) (^) c. Quality constraint d. None of these options ANS: C PTS: 1 MSC: AACSB: Analytic
- The constraints in a blending problem can be specified in a valid way and still lead to which of the following problems? a. Unboundedness b. Infeasibility (pg. 333) (^) c. Nonlinearity d. None of these options ANS: C PTS: 1 MSC: AACSB: Analytic
- To specify that must be at most 75% of the blend of , , and , we must have a constraint of the form a.
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d. e. ANS: C PTS: 1 MSC: AACSB: Analytic
- The problem which deals with the direct distribution of products from supply locations to demand locations is called a(n) (pg. 335). a. transportation problem -No shipments between origins or destinatisn are allowed. b. assignment problem c. network problem d. transshipment problem ANS: A PTS: 1 MSC: AACSB: Analytic
- The objective in transportation problems is typically to: a. maximize profits b. maximize revenue c. minimize costs (pg. 334) d. maximize feasibility ANS: C PTS: 1 MSC: AACSB: Analytic Origins: location products are produced (pg. 334). Destinations: customer locations (p.334)
- A typical transportation problem requires which of the following sets of input numbers:
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a. Capacities, demands and flows b. Capacities, demands and unit shipping costs (pg.
c. Supplies, demands and flows d. Supplies, demands and arcs ANS: B PTS: 1 MSC: AACSB: Analytic
- Capacities (supplies)
- Demands (requireme nts)
- Unit Shipping & (production) costs
- Which of the following is not a required input for a typical transportation problem? (pg.
a. Capacities (or supplies)-indicated^ the^ MAX^ each^ plant^ can^ supply^ in^ a^ given^ Amt. of time. b. Demands-estimated from some type of forecasting model. c. Unit shipping (and possibly production) costs -originates from a transportation cost analysis. d. Distance from origins to destinations ANS: D PTS: 1 MSC: AACSB: Analytic
- The decision variables in transportation problems are: (pg. 336) a. profits b. costs c. flows d. capacities
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a. warehouses b. geographic locations c. flows d. capacities In transportation problems all "Flows" go from left to right --- from origins to desintations. ANS: C PTS: 1 MSC: AACSB: Analytic
- In formulating a transportation problem as linear programming model, which of the following statements are correct? (pg. 340) a. There is one constraint for each supply location b. There is one constraint for each demand location c. The sum of decision variables out of a supply location is constrained by the supply at that location d. The sum of decision variables out of all supply locations to a specific demand location is constrained by the demand at that location e. All of these options Flowbalance Constraints- are supply & demand constraints (pg. 340). ANS: E PTS: 1 MSC: AACSB: Analytic
- In a transshipment problem, shipments a. can occur between any two nodes (suppliers, demanders, and transshipment locations) b. cannot occur between two supply locations c. cannot occur between two demand locations
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d. cannot occur between a transshipment location and a demand location e. cannot occur between a supply location and a demand location ANS: A PTS: 1 MSC: AACSB: Analytic
- Transportation and transshipment problems are both considered special cases of a class of linear programming problems called a. minimum cost problems b. minimum cost network flow problems c. supply locations network problems d. demand locations network problems ANS: B PTS: 1 MSC: AACSB: Analytic
- A minimum cost network flow model (MCNFM) has the following advantage relative to the special case of a simple transportation model: a. a MCNFM does not require capacity restrictions on the arcs of the network b. the flows in a general MCNFM don’t all necessarily have to be from supply locations to demand locations c. a MCNFM is generally easier to formulate and solve d. All of these options ANS: B PTS: 1 MSC: AACSB: Analytic
- In a typical minimum cost network flow model, the nodes indicate a. roads b. rail lines c. geographic locations
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- The flow balance constraint for each transshipment node, in a minimum cost network flow model, takes the form a. Flow in Flow out + Net supply b. Flow out Flow in + Net supply c. Flow in = Flow out d. Flow out Flow in + Net supply e. Flow in Flow out + Net demand A Transhipment point is a location where goods simply pass through. (pg. 343-344). ANS: C PTS: 1 MSC: AACSB: Analytic
- In a minimum cost network flow model, the flow balance constraint for each supply node takes the form (^) (pg. 344) a. Flow in Flow out + Net supply b. Flow out Flow in + Net demand c. Flow in = Flow out d. Flow out Flow in + Net supply e. Flow in Flow out + Net demand ANS: D PTS: 1 MSC: AACSB: Analytic
- In a minimum cost network flow model, the flow balance constraint for each demand node takes the
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form (pg. 344) a. Flow out Flow in + Net supply b. Flow in Flow out + Net demand c. Flow in = Flow out d. Flow in Flow out + Net demand e. Flow out Flow in + Net demand ANS: B PTS: 1 MSC: AACSB: Analytic
- In aggregate planning models, which of the following statements are correct? (pg. 351-357). a. The number of workers available influences the possible production levels (pg. 354). b. We allow the workforce level to be modified each month through the hiring and firing of workers (p. 352). c. We eventually allow demand to be backlogged; that is, demand need not be met on time (pg. 357 d. All of these options ANS: D PTS: 1 MSC: AACSB: Analytic Aggregate. Plan Models: determine workforce levels & production schedules for multiperiod time horizons.
- Any integer program involving 0 – 1 variables with constraint(s) is called a knapsack problem.
SJ
a. thre e b. two c. one d. zero
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a. Only the objective function is not a linear function of the decision variables b. Only the constraints are not linear functions of the decision variables c. The objective function and/or the constraints are not linear functions of the decision variables d. All of these options ANS: C PTS: 1 MSC: AACSB: Analytic TRUE/FALSE
- Many of the most successful applications of optimization in the real world have been in the areas of scheduling, blending, logistics and aggregate planning. ANS: T PTS: 1 MSC: AACSB: Analytic
- When we solve a linear programming problem with Solver, we cannot guarantee that the solution obtained is an optimal solution. ANS: F PTS: 1 MSC: AACSB: Analytic
- Multiple optimal solutions are quite common in linear programming models. ANS: T PTS: 1 MSC: AACSB: Analytic
- If an LP problem is not correctly formulated, Solver will automatically indicate that it is infeasible when trying to solve it.
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ANS: F PTS: 1 MSC: AACSB: Analytic
- Integer programming (IP) models are optimization models in which all of the variables must be integers. ANS: F PTS: 1 MSC: AACSB: Analytic
- Solver may be unable to solve some integer programming problems, even when they have an optimal solution. ANS: T PTS: 1 MSC: AACSB: Analytic
- If Solver fails to find an optimal solution to an integer programming problem, we might be able to find a near optimal solution by increasing the tolerance setting. ANS: T PTS: 1 MSC: AACSB: Analytic
- The LP relaxation of an integer programming (IP) problem is the same model as the IP model except that some integer constraints are omitted. ANS: F PTS: 1 MSC: AACSB: Analytic
- The optimal solution to an LP problem was 3.69 and 1.21. If and were restricted to be integers, then 4 and 1 will be a feasible solution, but not necessarily an optimal solution to the IP problem.
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- The transportation model is a special case of the minimum cost network flow model (MCNFM). ANS: T PTS: 1 MSC: AACSB: Analytic
- In transportation problems, shipments between supply points or between demand points are possible. ANS: F PTS: 1 MSC: AACSB: Analytic
- In transportation problems, the three sets of input numbers that are required are capacities, demands and flows. ANS: F PTS: 1 MSC: AACSB: Analytic
- In network models of transportation problems, arcs represent the routes for getting a product from one node to another. ANS: T PTS: 1 MSC: AACSB: Analytic
- A good shipping plan uses as many cheap routes as possible, but ultimately is constrained by capacities and demands. ANS: F PTS: 1 MSC: AACSB: Analytic
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- Transshipment points are locations where goods neither originate nor end up, but goods are allowed to enter such points to be shipped out to their eventual destinations. ANS: T PTS: 1 MSC: AACSB: Analytic
