Simulation of a Queuing System of a Post Office in Anylogic Software

Ďutková, Silvia; Achimský, Karol; Dróździel, Paweł

doi:10.26552/com.c.2020.2.15-22

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…The numerous forms of queueing systems are represented by models. Each model's formula specifies how the corresponding queuing system should behave under certain scenarios [Dutkova et al, (2020)]. A queueing model is a technique for discovering the best way to manage a queueing system.…”

Section: Design Of M/m/c/~/~ Queueing Modelmentioning

confidence: 99%

Queueing System in Fair Price Shop of Kerala to Mitigate Waiting Time and Optimization of Servers

Sasi¹,

Subramanian²,

Ravichandran³

2023

INDJCSE

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Queues are a typical occurrence in everyday life, particularly during peak hours in Fair Price Shops (FPS), government offices, banks, post offices, super markets, hospitals, and clinics. The arrival rate, service rate, and server usage all play a role in the queueing process of any system. We expect a balance between waiting time and server utilization in an effective system, with the ideal being less waiting time and maximum server utilization. This paper investigates efficient queue management in FPS using M/M/C queueing model. The major goal of this research is to minimize customer waiting time in the FPS with the minimal number of servers. It demonstrates the application of the simulation modelling as a method for optimizing the number of servers in a specific FPS in Kerala, India. The model was developed to provide the outcomes of system parameters like arrival rate, waiting time and server utilization.

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Section: Design Of M/m/c/~/~ Queueing Modelmentioning

confidence: 99%

Queueing System in Fair Price Shop of Kerala to Mitigate Waiting Time and Optimization of Servers

Sasi¹,

Subramanian²,

Ravichandran³

2023

INDJCSE

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“…Pengukuran kinerja dilanjutkan untuk mengetahui urutan prioritas antrian dari empat (4) orang yang akan dilayani dalam antrian dengan melibatkan lima (5) orang pengambil keputusan termasuk di dalamnya adalah pimpinan dari manajemen antrian ini [23], [24], [29], [30]. Sebelum dilakukan proses normalisasi, langkah pertama yang harus dilakukan adalah membuat matrik rating kinerja dimana setiap pengambil keputusan (DM) menaksir preferensi suatu bobot kriteria untuk menentukan tingkat prioritas.…”

Section: ( ) ∑unclassified

Group Decision Support System (GDSS) dengan Metode Entropy untuk Menentukan Prioritas Antrian Layanan Rumah Sakit Menggunakan Multiple Channel Model (M/M/s)

Hidayat¹,

Malik²,

Nurmaini³

2020

JATISI

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Layanan sistem antrian di di Rumah Sakit mengalami masalah bahwa antrian layanan lebih lama dari pada pelayanan kesehatanya sendiri. Atas dasar hal tersebut dibutuhkan sebuah model yang mampu memberikan layanan antri yang tepat sasaran dan memberikan rasa keadilan kepada pengantri. Dalam paper ini digunakan 10 kriteria untuk menentukan prioritas antrian yakni: Faktor Risiko Penyakit, Biaya Perawatan, Tenaga Medis, Peralatan Kesehatan, Waktu tunggu, Jarak Domisili Pasien, Usia, Jenis Kelamin, Jumlah pasien yang dilayani diunit yang dituju dan Keputusan Pimpinan. Ke-10 kriteria ini agar diperoleh hasil yang lebih objektif dikombinasikan dengan Group Decision Making Tipe 2 (GDM2) dan metode entropy untuk mengevaluasi antrian model Multiple Channel Model (M/M/s). Jumlah loket layanan sangat berpengaruh terhadap jumlah antrian dan waktu layanan. Kesimpulan yang didapat bahwa menambah jumlah loket layanan sebanyak dua kali lipat dari akan memangkas 1/2 dari jumlah orang yang dilayani per-satuan waktu pada setiap jalur antrian terutama direntang waktu antara jam 8.00 wib s.d. 10.00 wib. Selain itu berdasarkan penilaian Decision Maker (DM) dalam kelompok pengambil keputusan, kriteria biaya adalah faktor paling penting atau kritis ketika memberikan prioritas layanan diikuti dengan kriteria keputusan pimpinan dan faktor risiko penyakit. Penambahan kategori-kategori penyakit yang berbahaya dalam sistem antrian dapat membuat sistem ini menjadi lebih baik.

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Investigation of Queuing Systems in System Structure Management

E. V.

2024

Financial Engineering

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Queuing theory is used to develop recommendations for constructing queuing systems efficiently, organizing the associated operations and functionalities, and regulating request flows for optimal performance. This paper presents a study of the income functional for two specific cases of controlled queuing systems: the M/G*/1/N* system for a controlled service duration and number of waiting spaces, and the G*/M/n/m queuing system with a controlled arrival flow. The construction of a controlled semi-Markov process and the construction of an income functional on its trajectories were used as the basis for this study. The task is to find the optimal control strategy in the given queuing systems. An algorithm for finding optimal strategies applicable to similar queuing systems to increase their functioning efficiency when controlling the system’s main characteristics was developed for both systems.

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Simulation of a Queuing System of a Post Office in Anylogic Software

Cited by 4 publications

References 19 publications

Queueing System in Fair Price Shop of Kerala to Mitigate Waiting Time and Optimization of Servers

Queueing System in Fair Price Shop of Kerala to Mitigate Waiting Time and Optimization of Servers

Group Decision Support System (GDSS) dengan Metode Entropy untuk Menentukan Prioritas Antrian Layanan Rumah Sakit Menggunakan Multiple Channel Model (M/M/s)

Investigation of Queuing Systems in System Structure Management

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