scholarly journals Small Queuing Restaurant Sustainable Revenue Management

2020 ◽  
Vol 12 (8) ◽  
pp. 3477
Author(s):  
Kwangji Kim ◽  
Mi-Jung Kim ◽  
Jae-Kyoon Jun
Keyword(s):  
South Korea ◽  
Revenue Management ◽  
Waiting Time ◽  
Equilibrium Points ◽  
Management Strategies ◽  
Queuing System ◽  
Utilization Rate ◽  
Trade Off ◽  
Average Waiting Time ◽  
Price Increases

When competitive small restaurants have queues in peak periods, they lack strategies to cope. However, few studies have examined small restaurants’ revenue management strategies at peak times. This research examines how such small restaurants in South Korea can improve their profitability by adapting their price increases, table mix, and the equilibrium points of the utilization rates, and reports the following findings based on the analysis of two studies. In Study 1, improving profitability by increasing prices should carefully consider the magnitude and timing. In Study 2, when implementing the table mix strategy, seat occupancy and profit also increase, and we further find the equilibrium points of the utilization rates. Under a queuing system, the utilization rate and average waiting time are also identified as having a trade-off relationship. The results provide insights into how managers of small restaurants with queues can develop efficient revenue management strategies to manage peak hours.

The Analysis of ATM Queuing Phenomenon on Campus

2012 ◽  
Vol 155-156 ◽  
pp. 1117-1121 ◽  
Author(s):  
Na Song ◽  
Zhi Qin Shang
Keyword(s):  
Commercial Bank ◽  
Waiting Time ◽  
Sojourn Time ◽  
Queue Length ◽  
Queuing System ◽  
Utilization Rate ◽  
Allocation Of Resources ◽  
Average Waiting Time ◽  
Quantity Index ◽  
Working Efficiency

The article focused on the study of the ATM of Industrial and Commercial Bank in Qinhuangdao. To achieve the purposes of improving customers’ satisfaction and optimizing the allocation of resources, the article calculated some major quantity index including average queue length and waiting queue length, average waiting time and sojourn time as well as utilization rate of the system, analyzed ATM working efficiency of queuing system and gave some suggestions for improvement.

Development of a Heuristics Model for Simplifying a Multi-Channel Queuing System

2011 ◽  
Vol 367 ◽  
pp. 647-652
Author(s):  
B. Kareem ◽  
A. A. Aderoba
Keyword(s):  
Waiting Time ◽  
Channel Model ◽  
Single Channel ◽  
Queuing System ◽  
Queuing Model ◽  
Average Waiting Time ◽  
Queuing Models ◽  
Significant Difference ◽  
Number Of Customers ◽  
Proportionality Principle

Queuing model has been discussed widely in literature. The structures of queuing systems are broadly divided into three namely; single, multi-channel, and mixed. Equations for solving these queuing problems vary in complexity. The most complex of them is the multi-channel queuing problem. A heuristically simplified equation based on relative comparison, using proportionality principle, of the measured effectiveness from the single and multi-channel models seems promising in solving this complex problem. In this study, six different queuing models were used from which five of them are single-channel systems while the balance is multi-channel. Equations for solving these models were identified based on their properties. Queuing models’ performance parameters were measured using relative proportionality principle from which complexity of multi-channel system was transformed to a simple linear relation of the form = . This showed that the performance obtained from single channel model has a linear relationship with corresponding to multi-channel, and is a factor which varies with the structure of queuing system. The model was tested with practical data collected on the arrival and departure of customers from a cocoa processing factory. The performances obtained based on average number of customers on line , average number of customers in the system , average waiting time in line and average waiting time in the system, under certain conditions showed no significant difference between using heuristics and analytical models.

scholarly journals Spectral expansion method for analysis of a system with shifted Erlang and hyper-Erlang distributions

2021 ◽  
Vol 24 (2) ◽  
pp. 55-61
Author(s):  
Veniamin N. Tarasov ◽  
Nadezhda F. Bakhareva
Keyword(s):  
Waiting Time ◽  
Queuing Theory ◽  
Expansion Method ◽  
Spectral Expansion ◽  
Queuing System ◽  
Erlang Distribution ◽  
Modern Theory ◽  
Calculation Formula ◽  
Average Waiting Time ◽  
Erlang Distributions

In this paper, we obtained a spectral expansion of the solution to the Lindley integral equation for a queuing system with a shifted Erlang input flow of customers and a hyper-Erlang distribution of the service time. On its basis, a calculation formula is derived for the average waiting time in the queue for this system in a closed form. As you know, all other characteristics of the queuing system are derivatives of the average waiting time. The resulting calculation formula complements and expands the well-known unfinished formula for the average waiting time in queue in queuing theory for G/G/1 systems. In the theory of queuing, studies of private systems of the G/G/1 type are relevant due to the fact that they are actively used in the modern theory of teletraffic, as well as in the design and modeling of various data transmission systems.

PERFORMANCE ESTIMATION OFM/DK/1 QUEUE UNDER FAIR SOJOURN PROTOCOL IN HEAVY TRAFFIC

2008 ◽  
Vol 23 (1) ◽  
pp. 61-74
Author(s):  
Yingdong Lu
Keyword(s):  
Markov Process ◽  
Waiting Time ◽  
Service Time ◽  
Infinitesimal Generator ◽  
Heavy Traffic ◽  
Queuing System ◽  
Performance Estimation ◽  
Processor Sharing ◽  
Average Waiting Time ◽  
Processor Sharing Queues

We study the performance of aM/DK/1 queue under Fair Sojourn Protocol (FSP). We use a Markov process with mixed real- and measure-valued states to characterize the queuing process of system and its related processor sharing queue. The infinitesimal generator of the Markov process is derived. Classifying customers according to their service time, using techniques in multiclass queuing system, and borrowing recently developed heavy traffic results for processor-sharing queues, we are able to derive approximations for average waiting time for the jobs.

scholarly journals ACEA: A Queueing Model-Based Elastic Scaling Algorithm for Container Cluster

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Kui Li ◽  
Yi-mu Ji ◽  
Shang-dong Liu ◽  
Hai-chang Yao ◽  
Hang Li ◽  
...  
Keyword(s):  
Resource Utilization ◽  
Waiting Time ◽  
Sudden Change ◽  
Solution Space ◽  
Performance Model ◽  
Utilization Rate ◽  
Queuing Model ◽  
Average Waiting Time ◽  
Elastic Scaling ◽  
The Relationship

Elastic scaling is one of the techniques to deal with the sudden change of the number of tasks and the long average waiting time of tasks in the container cluster. The unreasonable resource supply may lead to the low comprehensive resource utilization rate of the cluster. Therefore, balancing the relationship between the average waiting time of tasks and the comprehensive resource utilization rate of the cluster based on the number of tasks is the key to elastic scaling. In this paper, an adaptive scaling algorithm based on the queuing model called ACEA is proposed. This algorithm uses the hybrid multiserver queuing model (M/M/s/K) to quantitatively describe the relationship among number of tasks, average waiting time of tasks, and comprehensive resource utilization rate of cluster and builds the cluster performance model, evaluation function, and quality of service (QoS) constraints. Particle swarm optimization (PSO) is used to search feasible solution space determined by the constraint relation of ACEA quickly, so as to improve the dynamic optimization performance and convergence timeliness of ACEA. The experimental results show that the algorithm can ensure the comprehensive resource utilization rate of the cluster while the average waiting time of tasks meets the requirement.

scholarly journals Deskripsi Sistem Antrian pada Klinik Dokter Spesialis Penyakit Dalam

2012 ◽  
Vol 12 (1) ◽  
pp. 72
Author(s):  
Deiby T Salaki
Keyword(s):  
Direct Observation ◽  
Waiting Time ◽  
Arrival Rate ◽  
Queuing System ◽  
Queuing Model ◽  
Average Waiting Time ◽  
Number Of Patients

DESKRIPSI SISTEM ANTRIAN PADA KLINIK DOKTER SPESIALIS PENYAKIT DALAM ABSTRAK Penelitian ini dilakukan untuk mengetahui deskripsi sistem antrian pada klinik dokter internist. Pengumpulan data dilakukan secara langsung pada klinik dokter internist JHA selama 12 hari, selama 2 jam waktu pengamatan tiap harinya pada periode sibuk.. Model antrian yang digunakan adalah model (M/M/1) : (FIFO/~/~), tingkat kedatangan bersebaran poisson, waktu pelayanan bersebaran eksponensial, dengan jumlah pelayanan adalah seorang dokter, disiplin antrian yang digunakan adalah pasien yang pertama datang yang pertama dilayani, jumlah pelayanan dalam sistem dan ukuran populasi pada sumber masukan adalah tak berhingga.  Sistem antrian pada klinik ini memiliki kecepatan kedatangan pelayanan anamnesa rata-rata  menit 1 orang pasien datang, kecepatan kedatangan pelayanan pemeriksaan fisik rata-rata  menit 1 orang pasien datang, rata-rata waktu pelayanan anamnesa untuk  seorang pasien  menit, rata-rata waktu pelayanan pemeriksaan fisik untuk  seorang pasien  menit, peluang kesibukan  pelayanan anamnesa sebesar , peluang kesibukan  pelayanan pemeriksaan fisik sebesar , dan peluang pelayanan anamnesa menganggur sebesar , peluang pelayanan pemeriksaan fisik menganggur sebesar . Rata-rata banyaknya pengantri untuk anamnesa adalah  pasien sedangkan untuk pemeriksaan fisik  pasien, rata-rata banyaknya pengantri dalam sistem adalah  pasien, waktu rata-rata seorang pasien dalam klinik adalah  menit, waktu rata-rata seseorang pasien untuk antri adalah  menit. Kata kunci: Sistem Antrian, Klinik Penyakit Dalam  DESCRIPTION OF QUEUING SYSTEM AT THE INTERNIST CLINIC ABSTRACT This research determines the description of queuing system at the internist Clinic. Data collected by direct observation during 12 days and in 2 hours. Queuing model that used is model of (M/M/1): (FIFO /~/~). Based on the research, the clinic has 3.256 minutes per patient in average arrival rate for anamnesys, the average arrival rate for diaagnosys is 3.255 minutes per patient, average service speed for anamnesys is 2.675 minutes per patient, average service speed for diagnosys is 12.635 minutes, the probability of busy periods for anamnesys is 0.864, the probability of busy periods for diagnosys is 0.832 and probability of all free services or no patient in the anamnesys equal to 0.136, probability of all free services or no patient in the anamnesys equal to 0.168. The average number of patients in anamnesys queue is 5 patients, the average number of patients in diagnosys queue is 4 patients, the average number of patients in the system is 10 patients, the average waiting time in the system is 47.078 minutes and the average queuing time is 31.660 minutes. Keywords: Queuing system, internist clinic

scholarly journals ANALISIS SISTEM ANTREAN PADA LOKET PENDAFTARAN POLIKLINIK SPESIALIS DI RS BALIMED

2021 ◽  
Vol 10 (2) ◽  
pp. 70
Author(s):  
KADEK DITA SUGIARI ◽  
I WAYAN SUMARJAYA ◽  
KETUT JAYANEGARA
Keyword(s):  
Steady State ◽  
Waiting Time ◽  
Queuing Theory ◽  
Queuing System ◽  
State Condition ◽  
Steady State Condition ◽  
Average Waiting Time ◽  
Number Of Patients ◽  
Measures Of Performance

Hospital is one of the service facilities that is not free from queue problem. One example of this hospital is Balimed Hospital. At certain times, especially in the morning, there is a lineup of patients at the Balimed Hospital’s Specialist Polyclinic. In order to maximize service, it is necessary to analyze the queuing system by applying the queuing theory. This study focuses on queues at the Balimed Hospital’s Specialist Polyclinic in Internal Disease. After conducting the research, it was found that the model used at the Specialist Polyclinic in Internal Disease is . With this model, the queuing system at Balimed Hospital's Specialist Polyclinic in Internal Disease is in steady state condition because ???? < 1. The measures of performance for queuing system at Balimed Hospital’s Specialist Polyclinic in Internal Disease is the average number of patients in queue  is 0,1 patient or it can be said that there is almost no patient in queue because the value of  is close to 0, the average number of patients in system  is 1 patient, the average waiting time for patients in queue  is 1 minute, and the average time spent by patients start from queuing until being served  is 2,5 minutes. The queuing system has been effective, it can be seen from the short waiting time for patients.

scholarly journals Predicting Impacts of Climate Change on Northward Range Expansion of Invasive Weeds in South Korea

Plants ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1604
Author(s):  
Sun Hee Hong ◽  
Yong Ho Lee ◽  
Gaeun Lee ◽  
Do-Hun Lee ◽  
Pradeep Adhikari
Keyword(s):  
Climate Change ◽  
South Korea ◽  
Habitat Suitability ◽  
Management Strategies ◽  
Southern Region ◽  
Suitable Habitat ◽  
Invasive Weeds ◽  
Northern Regions ◽  
Suitable Habitats ◽  
Control And Management

Predicting the distribution of invasive weeds under climate change is important for the early identification of areas that are susceptible to invasion and for the adoption of the best preventive measures. Here, we predicted the habitat suitability of 16 invasive weeds in response to climate change and land cover changes in South Korea using a maximum entropy modeling approach. Based on the predictions of the model, climate change is likely to increase habitat suitability. Currently, the area of moderately suitable and highly suitable habitats is estimated to be 8877.46 km2, and 990.29 km2, respectively, and these areas are expected to increase up to 496.52% by 2050 and 1439.65% by 2070 under the representative concentration pathways 4.5 scenario across the country. Although habitat suitability was estimated to be highest in the southern regions (<36° latitude), the central and northern regions are also predicted to have substantial increases in suitable habitat areas. Our study revealed that climate change would exacerbate the threat of northward weed invasions by shifting the climatic barriers of invasive weeds from the southern region. Thus, it is essential to initiate control and management strategies in the southern region to prevent further invasions into new areas.

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