Optimization of a stochastic model having erratic server with immediate or delayed repair

Radhika Agarwal, Divya Agarwal, Shweta Upadhyaya, Izhar Ahmad*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


The thought to put forward a queuing model proposed in this work was its pertinence in everyday life wherever we can see the uses of computing and networking systems. Industrial software developers and system managers can consider the results of the model to evolve their system for better results. Here we present a novel queueing model having erratic server with delayed repair and balking. Two distinct breakdowns i.e. active and passive breakdown for the system are also considered with their respective amendments. This model is closely related with the smooth functioning of the system during some internal faults (virus attack, electricity failures etc.). The performance indicators which are utilized in enhancing the service standards are obtained using supplementary variable technique. Using ANFIS soft computing technique we have compared the analytical results with those of neuro fuzzy results. Furthermore single and bi-objective minimization problems are considered and minima is obtained using particle swarm optimization and multi objective genetic algorithm respectively. Also, the minimization problems are shown as a convex programming problem to ensure the global optimality of the result. The proposed approach makes it conceivable to accomplish a relevant harmony between operational expenses and administration quality.

Original languageEnglish
JournalAnnals of Operations Research
StateAccepted/In press - 2022

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.


  • Active–passive breakdown
  • Balking
  • Bi-objective optimization
  • Convex programming problem
  • Delayed repair
  • Particle swarm optimization

ASJC Scopus subject areas

  • Decision Sciences (all)
  • Management Science and Operations Research


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