Cost inspection of a Geo/G/1 retrial model using particle swarm optimization and Genetic algorithm

Geetika Malik · Shweta Upadhyaya · Richa Sharma

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Advanced Queuing Theory Analysis Optimization and Search Problems Age of Information Optimization

Abstract

We have studied a Geo/G/1 retrial model with state-dependent and voluntary services in discrete-time frame. The concept of Bernoulli vacation is also considered wherein, after the execution of each service, the server may hold back for next unit or it may leave for a vacation of arbitrary duration. Priority and impatient units are also analysed. This system is applicable in digital and communication fields where the data is transferred in packets like broadband integrated services digital network (B-ISDN) and all those areas where time is considered as a discrete random variable. All necessary performance indices are established for the developed model. Stochastic decomposition laws for the system size are also provided. The calculated results are verified by performing numerical examples and a detailed illustration. We have further carried out a comparative analysis to obtain minimum cost using direct search method (DSM), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) techniques.

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References

2004A Discrete-Time Geo /G/1 Retrial Queue with General Retrial Times 2016Strategic behavior and social optimization in a constant retrial queue with the N -policy 2017On an unreliable-server retrial queue with customer feedback and impatience 1995On the steady-state queue size distribution of the discrete-timeGeo/G/1 queue with repeated customers 2012A discrete-time Geo/G/1 retrial queue with preferred and impatient customers 2006Discrete-time Geo/G/1 retrial queue with general retrial times and starting failures 2008A discrete time retrial queue with general retrial times and balking customers

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2022Optimal Cost Analysis for Discrete-Time Recurrent Queue with Bernoulli Feedback and Emergency Vacation

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