Analysis of a two-phase queue system with &lt;p,F&gt;-policy

Yeh, Chih-Shen; Lee, Yu-Tang; Chang, Chia‐Jung; Chang, Fu‐Min

doi:10.1080/16843703.2016.1208489

Cited by 13 publications

(6 citation statements)

References 23 publications

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“…Apart from that, several research problems can be found in the queueing literature on the controllable queues (cf. Chang and Ke (2011);Efrosinin D. V. et al (2018); Shekhar et al (2017); Yang and Wang (2013); Yang et al (2010;Yeh et al (2017)), which put the controlling policy in the context of Markovian/Non-Markovian queueing system. Recently, Chen (2018) studied the finite population machining system and performed the sensitivity investigation for reliability and mean-time-to-first-failure (MTTFF).…”

Section: Control Policiesmentioning

confidence: 99%

Optimal management strategies of renewable energy systems with hyperexponential service provisioning: an economic investigation

Varshney,

Shekhar,

Dhanunjaya Reddy

et al. 2023

Front. Energy Res.

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The current research proposes optimal management strategies for queueing modeling-based renewable energy systems with hyper-exponentially distributed maintenance/repair under the assumption of an admission control policy. Using the concept and steps of the matrix-analytical method, the steady-state probability distribution associated with energy systems is explicitly presented. A relatively straightforward computation that can help with modeling wind energy generation, investigating wind farm performance, optimizing energy based on system storage, reliability inspection, service maintenance planning, and numerous other purposes can be employed to mathematically derive several system performance indicators. The investigation findings are validated via quantitative outcomes, illustrative possesses, and a step-by-step recursive methodology for efficient management of the renewable energy system. Additionally, considering multiple governing parameter values, the nature-inspired optimization technique, Cuckoo Search (CS), is employed to demonstrate the optimum anticipated cost of renewable energy system. A comparison with other metaheuristics and semi-classical approaches is also presented to establish the best convergence results. In order to help system designers, policymakers, engineers, and researchers, several numerical examples are also provided to construct more practical strategies based on the production of energy, storage, and system management. The economic, parametric, and performance investigation findings are highlighted, and the opportunities and recommendations for further research are provided. In a nutshell, the outcomes of the present analysis can be adopted to formulate the most effective economic strategies and regulate decision-making processes in the energy sectors.

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Section: Control Policiesmentioning

confidence: 99%

Optimal management strategies of renewable energy systems with hyperexponential service provisioning: an economic investigation

Varshney,

Shekhar,

Dhanunjaya Reddy

et al. 2023

Front. Energy Res.

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“…In recent years, some researchers have contributed to the controlling of the admission of jobs in the system based on F -policy [14,6,39,7,15,18]. Yeh et al [41] developed a finite capacity single server Markovian queueing model under the policy and established the steady-state analytical formulae for various performance indices. The machine repair problem was investigated by Jain and Sanga [16,17] by considering the arrivals of failed machines to the repair facility as per F -policy.…”

Section: Madhu Jain and Sudeep Singh Sangamentioning

confidence: 99%

Admission control for finite capacity queueing model with general retrial times and state-dependent rates

Jain¹,

Sanga²

2020

Journal of Industrial &Amp; Management Optimization

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The finite state dependent queueing model with F-policy is investigated by considering the general retrial attempts. On arrival in the system, if the job finds the server engaged, it is forced to enter into the retrial orbit. After a random period of time, the job from the retrial orbit re-attempts for the service. According to F-policy, as the system attains its full capacity, the arrivals are restricted to join the system until the number of jobs comes down to the prefixed threshold value 'F '. The supplementary variable corresponding to the remaining retrial time is used to frame the governing equations which are solved by using Laplace-Stieltjes transform and then applying the recursive method. Special models for machine repair and time-sharing queue are deduced by setting the state dependent rates. Several system indices are obtained explicitly which are further used to facilitate the sensitivity analysis by considering a numerical illustration. A cost function is constructed and minimized for evaluating the optimal threshold parameter and optimal service rate.

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“…Randomized control of N -policy [5,6,14,19,20,[23][24][25] Randomized control of T -policy [12,19,21,26] Randomized control of F -policy [3,4,6,24,29] examined by [13]. For the F -policy M/H 2 /1/K queue with server breakdowns and exponential startup times, [1] formulated an optimization problem to determine the optimal capacity, the optimal threshold, the optimal startup rate, and the optimal repair rate at the minimum expected cost per unit time.…”

Section: Randomized Control Policy Studymentioning

confidence: 99%

Randomized control of arrivals in a finite-buffer GI/M/1 system with starting failures

Yang

2020

RAIRO-Oper. Res.

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This paper proposes a randomized policy for the control of arrivals in a finite-buffer GI/M/1 system with a single server. When the capacity of system is full, no new arrivals are permitted to enter the system. When the number of customers in the system decreases to threshold F , a new arriving customer is allowed to join the system with probability p. The system requires an exponential startup time before allowing customers to enter the system. The startup process may not be successful and is then restarted once again. Using the supplementary variable technique in a recursive process, we obtain the stationary distribution of the system size. Various performance measures of the system are developed. We also create a cost model based on the system performance measures and cost elements. The optimal threshold, optimal capacity and optimal startup rate of the system are determined to minimize the expected cost per unit time. Finally, we provide numerical examples to conduct a sensitivity analysis.Mathematics Subject Classification. 90B22, 60K25.

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Analysis of a two-phase queue system with <p,F>-policy

Cited by 13 publications

References 23 publications

Optimal management strategies of renewable energy systems with hyperexponential service provisioning: an economic investigation

Optimal management strategies of renewable energy systems with hyperexponential service provisioning: an economic investigation

Admission control for finite capacity queueing model with general retrial times and state-dependent rates

Randomized control of arrivals in a finite-buffer GI/M/1 system with starting failures

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