Topic VI. Multiple-Channel Queuing Model (Limited queue length system)

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Presentation transcript:

Topic VI. Multiple-Channel Queuing Model (Limited queue length system) Olga Marukhina, Associate Professor, Control System Optimization Department, Tomsk Polytechnic University Marukhina@tpu.ru

Next client did not get into the system Only three chairs for waiting Multichannel, single-phase waiting lines are found in many banks today: A common line is formed, and the customer at the head of the line proceeds to the first free teller. Next client did not get into the system Only three chairs for waiting A hairdresser Multiserver systems have parallel service providers offering the same service. Multiserver examples include grocery stores (multiple cashiers), drive-through banks (multiple drive-through windows), and gas stations (multiple gas pumps).

Model D (M/M/c): ( /N/ ) Multi-Channel Queuing Model with Poisson Arrivals and Exponential Service Times with a finite queue The service system can accommodate N customers only. The (N+c)th customer will not join the queue. c – number of channels. m (= N – c) – capacity of the queue. Due to restriction in the allowable number of customers in the system, the service system will be interested to know the expected number of customers who are lost. This can be found out by determining the probability of customers not joining the system.

Probability of 0 units in the system (that is, the service unit is idle) Probability of k channels are busy

Probability of all channels (=c) are busy and s units in the line Probability of failure of the service (is equal to the probability that the queue already are m units), system is full.

Probability of all channels (=c) are busy and s units in the line The average number of units in line waiting for service.

Remember!

Example I The arrival rate of cars at GRAND jewelers is 20 cars per hour. There are 2 services. Service rate at jeweler shop is 18 cars per hour (for each service). The only parking area at GRAND jewelers is restricted to 6 cars only. The arrival rate and service rate follows Poisson distribution. Identify the type of queue and then determine the performance measures of this queue. = 20 cars per hour; µ = 18 cars per hour; c = 2; m = 6 cars.

Compare the results 1 channel 2 channels p0 0.1019 0.505 pN 0.1917   1 channel 2 channels p0 0.1019 0.505 pN 0.1917 0.009 E 16.166 19.817 Lq 2.512 0.783 Wq 0.1553 0.039 Ls 3.41 1.894 Ws 0.2109 0.096

GPSS model

Arena model

The Winter Park Hotel Donna Shader, manager of the Winter Park Hotel, is considering how to restructure the front desk to reach an optimum level of staff efficiency and guest service. At present, the hotel has five clerks on duty, each with a separate waiting line, during peak check-in time of 3:00 P.M. to 5:00 P.M. Observation of arrivals during this period shows that an average of 90 guests arrive each hour (although there is no upward limit on the number that could arrive at any given time). It takes an average of 3 minutes for the front-desk clerk to register each guest. Ms. Shader is considering three plans for improving guest service by reducing the length of time that guests spend waiting in line. The first proposal would designate one employee as a quick-service clerk for guests registering under corporate accounts, a market segment that fills about 30% of all occupied rooms. Because corporate guests are preregistered, their registration takes just 2 minutes. With these guests separated from the rest of the clientele, the average time for registering a typical guest would climb to 3.4 minutes. Under this plan, noncorporate guests would choose any of the remaining four lines. The second plan is to implement a single-line system. All guests could form a single waiting line to be served by whichever of five clerks became available. This option would require sufficient lobby space for what could be a substantial queue. The use of an automatic teller machine (ATM) for check-ins is the basis of the third proposal. This ATM would provide about the same service rate as would a clerk. Because initial use of this technology might be minimal, Shader estimates that 20% of customers, primarily frequent guests, would be willing to use the machines. (This might be a conservative estimate if guests perceive direct benefits from using the ATM, as bank customers do. Citibank reports that some 95% of its Manhattan customers use its ATMs.) Ms. Shader would set up a single queue for customers who prefer human check-in clerks. This line would be served by the five clerks, although Shader is hopeful that the ATM machine will allow a reduction to four. Discussion Questions 1. Determine the average amount of time that a guest spends checking in. How would this change under each of the stated options? 2. Which option do you recommend?

Thank you for attention!