1) A goal of many waiting line problems is to help a firm

1) A goal of many waiting line problems is to help a firm

1) A goal of many waiting line problems isto help a firm find the ideal level of services that minimize the cost ofwaiting and the cost of providing the service.
2) One difficulty in waiting line analysisis that it is sometimes difficult to place a value on customer waiting time.
3) The goal of most waiting line problemsis to identify the service level that minimizes service cost.4) Two characteristics of arrivals are theline length and queue discipline.5) Limited calling populations are assumedfor most queuing models.
6) An “infinite callingpopulation” occurs when the likelihood of a new arrival depends upon the numberof past arrivals.
7) On a practical note — if we were tostudy the waiting lines in a hair salon that had only five chairs for patronswaiting, we should use an infinite queue waiting line model.
8) If we are studying the arrival ofautomobiles at a highway toll station, we can assume an infinite callingpopulation.
9) When looking at the arrivals at theticket counter of a movie theater, we can assume an unlimited queue.
10) Arrivals are random when they aredependent on one another and can be predicted.
11) On a practical note — if we are usingwaiting line analysis to study customers calling a telephone number forservice, balking is probably not an issue.
12) On a practical note — if we are usingwaiting line analysis to study cars passing through a single tollbooth,reneging is probably not an issue.
13) On a practical note — we shouldprobably view the checkout counters in a grocery store as a set of singlechannel systems.
14) A bank with a single queue to movecustomers to several tellers is an example of a single-channel system.15) Service times often follow a Poissondistribution.
16) An M/M/2 model has Poisson arrivalsexponential service times and two channels.
17) In a single-channel, single-phase system, reducingthe service time only reduces the total amount of time spent in the system, notthe time spent in the queue.18) The wait time for a single-channel system is more than twice that for a two-channel system using two servers working at the same rate as thesingle server.
19) The study of waiting lines is calledqueuing theory.
20) The three basic components of aqueuing process are arrivals, service facilities, and the actual waiting line.
21) In the multichannel model (M/M/m), wemust assume that the average service time for all channels is the same.
22) Queuing theory had its beginning inthe research work of Albert Einstein.
23) The arrivals or inputs to the systemare sometimes referred to as the calling population.
24) Frequently in queuing problems, the numberof arrivals per unit of time can be estimated by a probability distributionknown as the Poisson distribution.25) An automatic car wash is an example ofa constant service time model.26) Balking customers are those who enterthe queue but then become impatient and leave without completing thetransaction.27) In a constant service time model, boththe average queue length and average waiting time are halved.
28) A hospital ward with only 30 bedscould be modeled using a finite population model.
29) A finite population model differs froman infinite population model because there is a random relationship between thelength of the queue and the arrival rate.
30) A transient state is the normaloperating condition of the queuing system.
31) A queue system is in a transient statebefore the steady state is reached.32) Little’s Flow Equations are applicablefor single-channel systems only.
33) Little’s Flow Equations areadvantageous because if one characteristic of the operating system is known,the other characteristics can be easily found.
34) Using a simulation model allows one toignore the common assumptions required to use analytical models.
35) If we are using a simulation queuing model,we still have to abide by the assumption of a Poisson arrival rate, andnegative exponential service rate.

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