Biofuel production from biomass resources can significantly contribute to greenhouse gas mitigation and clean energy generation. This paper aims to develop a new decision analysis approach under an intuitionistic fuzzy set (IFS) setting to rank suitable biomass resources for biofuel production. For this purpose, an intuitionistic fuzzy Symmetry Point of Criterion (IF-SPC) tool was introduced to obtain the objective weight of the indicators and an IF-rank sum (IF-RS) was applied to find the subjective weight of the indicators under an IFS setting. Then, an integrated multi-attributive ideal real comparative assessment (MAIRCA) approach was introduced using aggregation operators and a proposed weight-determining tool to rank suitable biomass resources for biofuel production. Further, the usability of the proposed model was tested with a case study of the selection of biomass resources for biofuel production under the context of IFS. From the obtained outcomes, we found that the most important indicators for selecting suitable biomass resources for biofuel production are cost of biomass supply (EC-3), maturity (T-3), local acceptability (SP-1), cost of the biomass conversion process (EC-2), and reduction of GHG emissions (EN-1), respectively. From this perspective, globally existing sustainable biomass resources for biofuel production were recognized and then ranked over thirteen diverse indicators including environmental, economic, technical, and social-political pillars of sustainability. It was found that municipal solid waste and sewage, forest and wood farming waste, and livestock and poultry waste achieve higher overall utility scores over the other biomass resources for biofuel production in India. Furthermore, comparison with extant models and sensitivity analysis are discussed to present the usefulness and stability of the presented model.

In this paper an M/M/1 queueing system with server vacation, Startup, breakdowns and second optional service with impatient customer behavior is considered. All the customers will be given unique type of individual service in the first phase and then second phase service will be provided on option of the customer. We obtain some important system characteristics, such as the number of customers in the system, the probability that the server is idle, busy and broken down states, the expected waiting time in the system. Sensitivity analysis is also conducted with various parameters on system’s performance measures.

This paper deals the transient analysis of a queueing system with working vacation in which the server may encounter with breakdowns. Customers enter in batches according to a Poisson process and receive service in FCFS mode. Whenever the server finds nobody, the server starts a working vacation during which the server renders service at a slower rate than the normal one. Further, we considered two types of customer’s impatience balking and reneging. We solved the system of differential equations to find transient state probabilities and computed various performance indices like average queue length of system, the mean waiting time etc. We then executed sensitivity analysis and observed the impact on different parameters.

This article presents optimalstrategy N-Policy M/E_k/1 vacation queueingsystem when the server is in Start-up, Time-out and Breakdown for two-phase. The individual arrivals considered to follow Poisson process and receive batch service of k-stages in the first phase, individual service in the second phase. During the service arrivals are allowed to enter the batch. On completion of the second phase service to all customers in the second phase, the server come back to the first phaseand do the service to the customers who have arrived by providing them first phase service of k-stages followed by second phase service. If there is no customer waiting in the phase one service, the server waits for a fixed time ‘C’ is called server Time-out. If units arrived during this fixed time, then the server provides first phase followed by second phase service, otherwise after expiration of fixed time he takes a vacation. After N-customers accumulate in the system the server returns from vacation. Before going to first phase service, the server spends a random startup period for pre-service after coming back from vacation. During individual service the server is susceptible to random breakdown according to a Poisson process and the repair time follows an exponential distribution. After repair the server resumes individual service. Exact notations for steady state distribution of the number of customers in the system are derived. Developed a cost model for determining the optimal operating policy at a minimum cost. By using numerical illustrations the sensitivity analysis is also presented.