ANFIS and metaheuristics for double orbit retrial queue with complete and working vacations

The performance analysis of a double orbit retrial queue that incorporates impatience behaviour of the customers, feedback, complete vacation and working vacation has been investigated. The server opts for the complete vacation or working vacation after serving the customers of premium orbit or ordinary orbit, respectively. The probability generating approach has been implemented to obtain the performance metrices of the concerned queueing model. To obtain the steady state probabilities of individual system state, the maximum entropy principle has been employed. The joining strategy for the cooperative and non-cooperative cases have been discussed. The numerical experiment has been conducted to validate the analytical results. Furthermore, ANFIS approach is used so as to compare the numerical results obtained using analytical approach with ANFIS results. The optimal social net benefit and optimal joining probability have been computed using metaheuristics particle swarm optimization (PSO) and grey wolf optimizer (GWO). •Double orbit retrial queue with discouragement, feedback and hybrid vacation.•Implementation of Probability Generating Function and MEP.•Optimal social net benefit and optimal joining probability using PSO and GWO.•Sensitivity analysis and ANFIS Computing.