Cost optimization of a M/M/1/W V &MAV queueing system using Newton–Raphson and particle swarm optimization techniques

• Autorzy: Remya Ramachandran , Bouchentouf Amina Angelika , Kalidass Kaliappan

Identyfikatory

DOI

10.37190/ord240311

• Języki publikacji: EN

Abstrakty

EN

This paper is concerned with the optimal control of a Markovian queueing system subjected to multiple adaptive vacation and working vacation policies. This system is applicable in diverse modern technologies, in particular in call centers. We establish the steady-state solution as well as important system characteristics by means of probability generating functions technique. We also construct the expected total cost for this model and develop a procedure to determine the optimal service rate that yields the minimum cost. Further, we carried out a comparative analysis to obtain the minimum cost using the Newton–Raphson method and particle swarm optimization (PSO) algorithm.

Słowa kluczowe

EN

Markovian queue; working vacation; adaptive vacations; cost model; optimization

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Operations Research and Decisions
• Rocznik: 2024
• Tom: Vol. 34, No. 3
• Strony: 205--220
• Opis fizyczny: Bibliogr. 37 poz., rys.

Twórcy

autor

Remya Ramachandran

• Department of Mathematics, Karpagam Academy of Higher Education, Coimbatore-641 021, Tamil Nadu, India

• https://orcid.org/0009-0008-1392-0398

autor

Bouchentouf Amina Angelika

• Mathematics Laboratory, Djillali Liabes University of Sidi Bel Abbes, Laboratory of Stochastic Models, Statistic and Applications, University of Saida – Dr. Moulay Tahar, Algeria

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

autor

Kalidass Kaliappan

• Department of Mathematics, Karpagam Academy of Higher Education, Coimbatore-641 021, Tamil Nadu, India
• Department of Mathematics, Chikkanna Government Arts College, Tirupur-641 602, Tamil Nadu, India

• https://orcid.org/0000-0002-1814-6118

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).