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

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Remya R., Bouchentouf A. A., Kalidass K.
Operations Research and Decisions
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2024
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vol. 34
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issue 3
205-220
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.
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A queueing model for an automatic manufacturing system with disasters, breakdowns, and vacations : optimal design and analysis

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Yatim N. R., Bouchentouf A. A., Laxmi P. V.
Operations Research and Decisions
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2024
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vol. 34
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issue 4
231-250
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.
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