A queueing model for an automatic manufacturing system with disasters, breakdowns, and vacations : optimal design and analysis

• Autorzy: Yatim Nada Riheb , Bouchentouf Amina Angelika , Laxmi Pikkala Vijaya

Identyfikatory

DOI

10.37190/ord240413

• Języki publikacji: EN

Abstrakty

EN

We study a queueing model with disasters, working breakdowns, balking, reneging, and vacations. This is a novel and realistic queueing model that captures the complex dynamics and behaviors of an automatic manufacturing system (AMS) with various uncertainties and disruptions. The system loses all customers when a disaster occurs and repairs start immediately. New customers get slower service during breakdowns. We use matrix methods to find the system’s steady state along with performance measures like the expected number of customers lost, the expected waiting time, and system reliability. We also optimize the system parameters (system capacity, number of servers, service rates) to minimize the cost function using a combined direct search method and quasi-Newton method. Our results can enhance the AMS’s performance, profit, and customer satisfaction.

Słowa kluczowe

EN

queueing models; disasters; customers' impatienc; vacation; Q-matrix method; optimization

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Operations Research and Decisions
• Rocznik: 2024
• Tom: Vol. 34, No. 4
• Strony: 231--250
• Opis fizyczny: Bibliogr. 33 poz., rys.

Twórcy

autor

Yatim Nada Riheb

• Laboratory of Stochastic Models, Statistic and Applications, University of Saida-Dr. Moulay Tahar, Saida, Algeria

autor

Bouchentouf Amina Angelika

• Laboratory of Mathematics, Djillali Liabes University of Sidi Bel Abbes, 22000 Sidi Bel Abbes, Algeria

• https://orcid.org/0000-0001-8972-4221

autor

Laxmi Pikkala Vijaya

• Department of Applied Mathematics, Andhra University, Visakhapatnam, India

• https://orcid.org/0000-0002-8721-5148

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).