数据模型与决策 第二版 课后答案 ([美]希利尔 Hillier) 第15章参考答案.doc

15-1CHAPTER 15COMPUTER SIMULATION: BASIC CONCEPTSReview Questions15.1-1 Computer simulation imitates the operation of a stochastic system by using the corresponding probability distributions to randomly generate the various events that occur in the system.15.1-2 Computer simulation typically takes a lot of time and effort, which tends to be relatively expensive.15.1-3 Computer simulation typically is used when the stochastic system involved is too complex to be analyzed satisfactorily by mathematical models.15.1-4 A random number is a number between 0 and 1 which is generated in such a way that every possible number within this interval has an equal chance of occurring. These numbers are then used to generate random occurrences from probability distributions.15.1-5 The inverse transformation method is a method for generating random observations from a probability distribution. The first step is to generate a uniform random number r. The second step is to find the value of x such that F(x)=r. The value of x is the desired random observation from the probability distribution.15.2-1 Herr Cutter must decide whether or not to hire an associate.15.2-2 The first rule of thumb is that in a well run barbershop with a long-established clientele, these loyal customers are willing to tolerate an average waiting time of about 20 minutes until the haircut begins. The second rule of thumb is that in a well run barbershop, new customers are willing to tolerate an average waiting time of about 10 minutes before the haircut begins.15.2-3 The probability distributions for service times and interarrival times need to be estimated.15.2-4 Uniform random numbers and the inverse transformation method are used to generate random observations from these distributions.15.2-5 A simulation clock is a variable in the computer program that records how much simulated time has elapsed.15.2-6 The main procedure for advancing the time on the simulation clock is called next-event time advance.15.2-7 The state of the system is N(t)=number of customers in the system at time t.15.2-8 The only difference comes when the next-event time-advance procedure is determining which event occurs next. Instead of just two possibilities for this next event, there are three.15-215.3-1 Fritz began by simulating the current operation of the shop. This was largely to test the validity of his simulation model.15.3-2 The Queueing Simulator obtains a point estimate and a 95% confidence interval.15.3-3 Fritz compared the results from the simulation run with the analytical results available. He also asked Herr Cutter whether the numbers seem consistent with what he has been experiencing in the barbershop.15.3-4 Fritz’s simulation model assumes that the system has an infinite queue and that once started, the system operates continually without ever closing and reopening. A simulation model does not need to be a completely realistic representation of the real system.15.3-5 It is estimated that Herr Cutter’s income would eventually increase if he adds an associate.15.4-1 The case study is an example of queueing system simulation.15.4-2 The management science team simulated various redesigns of the company’s entire supply chain.15.4-3 The probability of meeting a deadline is being estimated when computer simulation is used to supplement the PERT three-estimate approach.15.4-4 How many machines of each type should be provided?15.4-5 A new distribution system with central dispatching was being designed.15.4-6 Computer simulation provides a probability distribution of the return from the investment.15.4-7 Simulating the use of hospital resources when treating patients with coronary heart disease has been done.15.4-8 An automated system to handle mail was being planned. It was projected to achieve labor savings of over $4 billion per year.15.5-1 The management science team needs to begin by meeting with management.15.5-2 A simulation model often is formulated in terms of a flow diagram.15.5-3 Before constructing a computer program, the management science team should engage the people most intimately familiar with how the system will operate in checking the accuracy of the simulation model.15.5-4 A general-purpose simulation language is capable of programming almost any kind of simulation model. Applications-oriented simulators are designed for simulating fairly specific types of systems.15.5-5 In an animation, key elements of a system are represented in a computer display by icons that change shape, color or position when there is a change in the state of the simulation system.15.5-6 Will the measures of performance for the real system be closely approximated by the values of these measures generated by the simulation model?15-315.5-7 Each simulation run can be viewed as a statistical experiment that is generating statistical observations of the performance of the simulated system.15.5-8 The output from the simulation run now provide statistical estimate。