ANFIS simulation integrated in FM/FM/1/(CV + WV) queue with Bernoulli service interruption and metaheuristic optimization for mathematical model.

The present investigation studies performance modeling and analysis of an M/M/1 queue with a hybrid vacation policy and Bernoulli service interruption. When the system becomes empty, the server has the choice to switch over to a complete vacation state or a working vacation state. During working vacations, the server also serves customers through a Bernoulli service process at a slower rate. After completing the service, the server either transitions to a normal busy state or remains in the working vacation state. To analyze the performance of the system, we have developed a Markovian queueing model by formulating the Chapman–Kolmogorov governing equations for the system states. Through an iterative and difference-differential equation approach, we derived the stationary probability distribution of the queue size, along with other key queueing metrics such as average queue length, average waiting time, and throughput. To deal with a more practical scenario of imprecise information about the system descriptors, the proposed crisp queueing is transformed into a fuzzy model by retaining the features. The soft computing approach based on adaptive neuro-fuzzy inference system (ANFIS), -cut, and parametric nonlinear programming (PNLP) is employed to obtain various fuzzified indices. Moreover, to determine the optimal service rate, the differential evolution (DE) and golden section search (GSS) methods are used. By taking illustration, the proposed optimization techniques are implemented to develop a cost-effective service system and to examine the sensitivity of the key descriptors. [ABSTRACT FROM AUTHOR]