CHAPTER 10
SIMULATION MODELING
SOLUTIONS TO DISCUSSION QUESTIONS
10-1. Advantages of simulation: (1) relatively straightforward; (2) can solve large, complex problems; (3)
(1) cost; (2) no optimal solutions; (3) managers must generate conditions to test; (4) each model is unique.
10-2.
(a) Inventory ordering policy: May require simulation if lead time and daily demand are not constant.
Simulation is also useful if data do not follow traditional probability distribution.
10-3. Problems with conditions of certainty can be solved more easily by other decision modeling
10-4. Major steps are: (1) define problem, (2) introduce important variables, (3) construct model, specify
values to test, (4) conduct simulation, (5) examine results, (6) select best plan.
10-5. When a system contains elements that exhibit chance in their behavior, the Monte Carlo method of
simulation may be applied. The basis of Monte Carlo simulation is experimentation on the chance (or
thousands or millions.
10-8. Simulation may very well increase in use for several reasons:
(2) simulation languages may be refined and made easier for non-computer-expert managers to use,
especially with the advent of spreadsheet approaches,
(4) complex problems will not become fewer in nature.
10-9. The result of a simulation model approaches the expected value (or average) of the output measure
10-10. A flow diagram shows the logic of the simulation process. That is, it shows the sequence in which
10-11. Three main reasons why using an add-in program is useful in simulation modeling are: (1) they
have built-in functions to simulate from a large number of probability distributions that may be difficult
10-13. Excel’s Solver requires a deterministic environment. That is, the input data values must be fixed,