Download presentation

Presentation is loading. Please wait.

Published byDimitri Belden Modified about 1 year ago

1

2
Model Antrian Ganda Pertemuan 21 Matakuliah: K0414 / Riset Operasi Bisnis dan Industri Tahun: 2008 / 2009

3
Bina Nusantara University 3 Learning Outcomes Mahasiswa akan dapat menghitung penyelesaian model antrian tunggal dan ganda dalam berbagai contoh aplikasi.

4
Bina Nusantara University 4 Outline Materi: Model Antrian Ganda M/M/C Jaringan Antrian Contoh Penerapan

5
Bina Nusantara University 5 Type: Multiple servers; single-phase. Input source: Infinite; no balks, no reneging. Queue: Unlimited; multiple lines; FIFO (FCFS). Arrival distribution: Poisson. Service distribution: Negative exponential. M/M/S Model

6
Bina Nusantara University 6 M/M/S Equations Probability of zero people or units in the system: Average number of people or units in the system: Average time a unit spends in the system: Note: M = number of servers in these equations

7
Bina Nusantara University 7 M/M/S Equations Average number of people or units waiting for service: Average time a person or unit spends in the queue:

8
Bina Nusantara University 8 M/M/2 Model Equations (2 + )(2 - ) W s = 44 4 L q = W q W q = 2 L s = W s P 0 = 2 - 2 + Average time in system: Average time in queue: Average # of customers in queue: Average # of customers in system: Probability the system is empty:

9
Bina Nusantara University 9 M/M/2 Example Average arrival rate is 10 per hour. Average service time is 5 minutes for each of 2 servers. = 10/hr, = 12/hr, and S=2 Q1: What is the average wait in the system? W s = 4 12 4(12) 2 -(10) 2 = hours = 6.05 minutes

10
Bina Nusantara University 10 M/M/2 Example = 10/hr, = 12/hr, and S=2 Q2: What is the average wait in line? Also note: so W s = 1 W q + W q = 1 W s -= = hrs W q = (10) 2 12 (2 )(2 ) = hrs = 1.05 minutes

11
Bina Nusantara University 11 M/M/2 Example = 10/hr, = 12/hr, and S=2 Q3: What is the average number of customers in line and in the system? L q = W q = 10/hr hr = customers L s = W s = 10/hr hr = customers

12
Bina Nusantara University 12 M/M/2 Example = 10/hr and = 12/hr Q4: What is the fraction of time the system is empty (server is idle)? = 41.2% of the time P 0 = 2

13
Bina Nusantara University 13 M/M/1, M/M/2 and M/M/3 1 server2 servers3 servers W q 25 min.1.05 min min. (8 sec.) hr hr hr W S 30 min.6.05 min min. L q cust cust cust. L S 5 cust.1.01 cust cust. P % 41.2% 43.2%

14
Bina Nusantara University 14 Service Cost per Day = 10/hr and = 12/hr Suppose servers are paid $7/hr and work 8 hours/day and the marginal cost to serve each customer is $0.50. M/M/1 Service cost per day = $7/ hr x 8 hr/day + $0.5/ cust x 10 cust/hr x 8 hr/day = $96/ day M/M/2 Service cost per day = 2 x $7/hr x 8 hr/day + $0.5 /cust x 10 cust/hr x 8 hr/day = $152/ day

15
Bina Nusantara University 15 Customer Waiting Cost per Day = 10/hr and = 12/hr Suppose customer waiting cost is $10/hr. M/M/1 Waiting cost per day = $10/hr x hr/cust x 10 cust/hr x 8 hr/day = $333.33/ day M/M/1 total cost = = $429.33/day M/M/2 Waiting cost per day = $10/hr x hr/cust x 10 cust/hr x 8 hr/day =$14/ day M/M/2 total cost = = $166/day

16
Bina Nusantara University 16 Unknown Waiting Cost Suppose customer waiting cost is not known = C. M/M/1 Waiting cost per day = Cx hr/cust x 10 cust/hr x 8 hr/day = 33.33C $/ day M/M/1 total cost = C M/M/2 Waiting cost per day = Cx hr/cust x 10 cust/hr x 8 hr/day =1.4C $/ day M/M/2 total cost = C M/M/2 is preferred when C < C or C > $1.754/hr

17
Bina Nusantara University 17 M/M/2 and M/M/3 Q: How large must customer waiting cost be for M/M/3 to be preferred over M/M/2? M/M/2 total cost = C M/M/3 Waiting cost per day = Cx hr/cust x 10 cust/hr x 8 hr/day = C $/ day M/M/3 total cost = C M/M/3 is preferred over M/M/2 when C < C C > $45.81/hr

18
Bina Nusantara University 18 = Mean number of arrivals per time period. –Example: 3 units/hour. = Mean number of arrivals served per time period. –Example: 4 units/hour. 1/ = 15 minutes/unit. Remember: & Are Rates If average service time is 15 minutes, then μ is 4 customers/hour

19
Bina Nusantara University 19 M/D/S –Constant service time; Every service time is the same. –Random (Poisson) arrivals. Limited population. –Probability of arrival depends on number in service. Limited queue length. –Limited space for waiting. Many others... Other Queuing Models

20
Bina Nusantara University 20

Similar presentations

© 2017 SlidePlayer.com Inc.

All rights reserved.

Ads by Google