Analysis of a finite buffer with non-preemptive priority scheduling

1999 ◽  
Vol 15 (2) ◽  
pp. 345-365 ◽  
Author(s):  
Dietmar Wagner ◽  
Udo R. Krieger
2018 ◽  
Vol 4 (2) ◽  
pp. 77-83
Author(s):  
Budiyantoro ◽  
Yusrila Yeka Kerlooza

Di perusahaan pakaian, jadwal produksi ditentukan secara periodik. Seringkali suatu jadwal yang telah ditentukan harus diubah secara tiba-tiba akibat permintaan pasar dan hal-hal lain yang bersifat penting secara pemasaran. Perubahan jadwal produksi harus diperhitungkan secara cermat, atau akan menyebabkan berkurangnya keuntungan potensial perusahaan. Perubahan jadwal produksi harus didasarkan pada perhitungan nilai prioritas yang baik. Penelitian ini mengungkapkan faktor-faktor penentu nilai prioritas produksi pakaian, yaitu: keuntungan potensial (K), tenggat waktu (Td), lama produksi (Tp), strategi marketing (m). Rumusan antara faktor-faktor tersebut juga telah berhasil dinyatakan secara jelas, yaitu: P = (K ∙ m) / (Td ∙ Tp). Penelitian ini juga merumuskan suatu metode penjadwalan produksi pakaian, Quantum-based dan Preemptive Priority Scheduling (QPPS) yang merupakan penggabungan dua algoritma penjadwalan task di sistem operasi, yaitu algoritma quantum-based round-robin dan preemptive priority scheduling. Berdasarkan model kasus pada penelitian ini, penggunaan perhitungan nilai prioritas dan strategi penjadwalan produksi pakaian metode QPPS berhasil meningkatkan keuntungan potensial sebesar 13,1 % dibandingkan metode konvensional.


2013 ◽  
Vol 224 (2) ◽  
pp. 324-332 ◽  
Author(s):  
Joris Walraevens ◽  
Tom Maertens ◽  
Herwig Bruneel

Our research objective is to reduce the Average Waiting Time for patients in an Emergency Department of public sector hospital. We have based our model on M/M/s Queuing System, our study revealssignificant findings on arrival rate of patients. During this simulation, we have used a preemptive priority scheduling model. In our practice, the arrival rate followed a Poisson distribution, averaging 30 patients per hour, with the Mean Service time of1.5 hours and Average Waiting Time recorded around 12.13 minutes. This research offersvaluable help to achieve better time management in emergency departments of high-density medical facilities.


Author(s):  
Varghese Jacob

This paper presents a retrial queueing system with customer induced interruption while in service. We consider a single server queueing system of infinite capacity to which customers arrive according to a Poisson process and the service time follows an exponential distribution.An arriving customer to an idle server obtains service immediately and customers who find server busy go directly to the orbit from where he retry for service. The inter-retrial time follows exponential distribution. The customer interruption while in service occurs according to a Poisson process and the interruption duration follows an exponential distribution. The customer whose service is got interrupted will enter into a finite buffer. Any interrupted customer, finding the buffer full, is considered lost. Those interrupted customers who complete their interruptions will be placed into another buffer of same size. The interrupted customers waiting for service are given non-preemptive priority over new customers. We analyse the steady-state behavior of this queuing system. Several performance measures are obtained. Numerical illustrations of the system behaviour are also provided with example.


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