1、附件 附件 外文翻译 英文 Waiting lines and simulation The “miss manners” article pokes fun at one of lifes realities； having to wait in line.no boubt those waiting in line would all agree that the solution to the problem is obvious；simply add more servers or else do something to speed up service.although both
2、edeas may be potential solutions,there are certain subleties that must be dealt with. For one thing, most service systems have the capacity to process more customers over the long run than they are called on to process. Hence,the problem of customers waiting is a short-term phenomenon. The other sid
3、e of the the coin is that at certain times the servers are idle, waiting for customers. Thus by increasing the service capacity, the server idle time would increase even more. Consequently,in designing service systems,the designer must weiht the cost of providing a given level of service capacity ag
4、ainst the potential(implicit) cost of having customers wait for service. This planning and analysis of service capacity frequently lends itself to queuing theory,which is a mathematical approach to the analysis of waiting lines. The foundation of modern queuing theory is based on studies about autom
5、atic dialing equipment made in early part of the twentieth century by Danish telephone engineer A.K.Erlang. Prior to World War II,very few attempts were made to apply queuing theory to business problems. Since that time, queuing theory has been applied to a wide range of problems. The mathematics of
6、 queuing can be complex；for that reason,the emphasis here will not be on the mathematics but the concepts that underlie the use of queuing in analyzing waiting-line problems. We shall rely on the use of formulas and tables for analysis. Waiting lines are commonly found wherever customers arrive rand
7、omly for services. Some examples of waiting lines we encounter in our daily lives include the lines at supermarkdt checkouts,fast-food restaurants,aipport ticket counters,theaters, post offices,and toll booths. In many situations, the “customers” are not people but orders waiting to be filled ,truck
8、s waiting to be unloaded,jobs waiting to be processed,or equipment awiting repairs. Still other examples include ships waiting to dock, planes waiting to land,hospital patients waiting for a nurse,and cars waiting at a stop sign. One reason that queuing analysis is important is that customers regard
9、 waiting as a 附件 non-value-added activity. Customers may tend to associate this with poor service quality，especially if the wait is long. Similarly, in an organizational setting, having work or employees wait is non-value-addedthe sort of waste that workers in JIT systems strive to reduce. The discu
10、ssion of queuing begins with an examination of what is perhaps the most fundamental issue in waiting-line theory:why is there waiting? Why is there waiting? Many people are surprised to learn that waiting lines tend to form even though a system is basically underloaded. For example, a fast-food rest
11、aurant may have the capacity to handle an average of 200 orders per hour and yet experience waiting lines even though the average number of orders is only 150 per hour. The key word is average. In reality,customers arrives at random intervals rather than at evenly spaced intervals,and some orders ta
12、ke longer to fill than others. In other words, both arrivals and service times exhibit a high degree of variability. As a result, the system at times becomes temporarily overloaded, giving rise to waiting lines；at other times, the systems is idle because there are no customers. Thus,although a syste
13、m may be underloaded from a macro standpoint, varialilities in arrivals and service mean that at times the system is overloaded from a micro standpoint. It follows that in systems where variability is minimal of nonexistent(e.g.,because arrivals can be scheduled and service time is constant),waiting
14、 lines do not ordinarily form. Managerial Implications of Waiting Lines Managers have a number of very good reasons to be concerned with waiting lines. Chief among those reasons are the following: 1. The cost to provide waiting space. 2. A possible loss of business should customers leave the line be
15、fore being served or refuse to wait at all 3.A possible loss of goodwill. 4.A possible reduction in customer satisfaction. 5.The resulting congestion may disrupt other business operations and/or customers. Goal of Waiting-Line Analysis The goal of queuing is essentially to minimize total costs. Ther
16、e are two basic categories of cost in a queuing situation: those associated with customers waiting for service and those associated with capacity. Capacity costs are the costs of maintaining the ability to provide service. Examples include the number of bays at a car wash, the number of chechkouts a
17、t a supermarket, the number of repair people to handle equipment breakdowns, and the number of lanes on a highway. When a service facility is idle, capacity is lost since it cannot be stored. 附件 The costs of customer waiting include the salaries paid to employees while they wait for service(mechanic
18、s waiting for tools,the drivers of trucks waiting to unload),the cost of the space for waiting(size of doctors waiting room,length of driveway at a car wash, fuel consumed by planes waiting to land),and any loss of business due to customers refusing to wait and possibly going elsewhere in the future
19、. A practical difficulty frequently encountered is pinning down the cost of customer waiting time, especially since major portions of that cost are not a part of accounting data. One approach often used is to treat waiting times or line lengths as a policy variable: A manager simply specifies an acc
20、eptable level of waiting and directs that capacity be established to achieve that level. The traditional goal of queuing analysis is to balance the cost of providing a level of service capacity with the cost of customers waiting for service. Figure 1 illustrates this concept. Note that as capacity i
21、ncreases, its cost increases. For simplicity, the increase is shown as a linear relationship. Although a step function is often more appropriate ,use of a straight line does not significantly distort the picture. As capacity increases,the number of customers waiting and the time they wait tend to de
22、crease, thereby decreasing waiting costs. As is typical in trade-off relationships, total costs can be represented as a U-shaped curve. The goal of analysis is to identify a level of service capacity that will minimize total cost.( Unlike the situation in the inventory EOQ model,the minimum point on
23、 the total cost curve is not usually where the two cost lines intersect. ) In situations where those waiting in line are external customers(as opposed to employees),the existence of waiting lines can reflect negatively on an organizations quality image. Consequently, some organizations are focusing
24、their attention on providing faster servicespeeding up the rate at which service is delivered rather than merely increasing the number of servers. The effect of this is to shift the total cost curve downward if the cost of customer waiting decreases by more than the cost of the faster service. C o s
25、 t 0O p t i m u m S e r v i c e c a p a c i t yC o s t o f c u s t o m e r s w a i t i n gT o t a l c o s t C o s t o f s e r v i c e c a p a c i t y Figure1: The goal of queuing analysis is to minimize the sum of two costs: customer waiting costs and service capacity cost. System Characteristics There are numerous queuing models from which an analyst can choose. Naturally, much of the success of
