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What are the mathematical models used to analyze controllable arrival rates in a queue system? 


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Mathematical models such as finite capacity, finite source, Markovian queueing models with despondent arrivals , fluid-flow models for queuing networks , Gt/GI/st+GI time-varying fluid models integrated with nonlinear integer programming , single-server retrial queues with event-dependent arrival rates , and single-server exponential queuing systems with arrival and service rates dependent on a Markov chain are utilized to analyze controllable arrival rates in queue systems. These models consider factors like system characteristics, occupancy regulation, inter-arrival time adjustments, event-dependent arrival rates, and state-dependent arrival and service rates to study the impact of controlled arrival rates on queue behavior, delays, and system performance. Each model offers unique insights into managing and optimizing arrival processes within queueing systems for improved efficiency and reduced congestion.

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The paper utilizes a single-server exponential queuing system with phase-dependent arrival and service rates modeled by a Markov chain, employing Neuts's matrix geometric approach for analysis.
Mathematical models in the paper analyze a single-server retrial queue with event-dependent arrival rates, focusing on stability conditions, stationary distribution, and performance measures under high retrial rates.
The paper utilizes the Gt/GI/st+GI time-varying fluid model and nonlinear integer programming to analyze and control aircraft inter-arrival times in a queue system.
The paper utilizes a fluid-flow model and sliding mode control approach with predictor-based feedback to regulate arrivals in queuing networks, ensuring desired queue lengths are maintained.
The mathematical model used is a finite capacity, finite source, Markovian queueing system with despondent arrivals, retainment of reneged customers, and controllable arrival rates.

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What are the key mathematical models and algorithms used in "Closed Networks of Queues" by R. J. Swersey (1967)?4 answersThe key mathematical models and algorithms used in "Closed Networks of Queues" by R. J. Swersey (1967) include queueing theory models, Markov chain C, fluid approximation, and stationary strategies. The paper discusses the use of queueing/waiting mathematical models to optimize production department size and production costs. It also presents the Markov chain C as a method to determine queue lengths stationary probabilities for open networks of queues. Additionally, the paper explores optimality conditions in closed networks using fluid approximation and steady-state strategies. These models and algorithms provide insights into minimizing costs, optimizing service rates, and improving resource utilization in closed networks of queues.
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