The study presents Proposed Data Envelopment Analysis (DEA) approaches for intelligent business analytics of the US Airline industry to gain more knowledge, control, flexibility and trade-off among various inputs to the system/industry. Three new proposed DEA models are presented. The results obtained provide credible data analytics and intelligent business suggestions. Firstly the proposed input oriented and the proposed output oriented DEA models are formulated. The proposed input oriented DEA model suggests how resource utilization can be minimized while operating in with the same output level. Further, the proposed output oriented model suggests how output efficiency can be increased to a benchmark level while keeping the input at the same level. Then the proposed Slack Based DEA model SBM is formulated. The proposed models are then solved with the DEA Excel Solver for finding the efficient points in the Pareto Frontier. Representing the Pareto Frontier as a function of total system revenue gives necessary information about the inputs growth and their trade-off with the output. Furthermore, the proposed Slack Based DEA model (SBM) intelligently measures the technical efficiency of each airline. The results show that three airlines namely American, United and Jet Blue are weakly efficient operating below the proposed SBM efficient frontier. Furthermore, the results intelligently suggest the possible inputs reduction and outputs increases to get to the efficient frontier for the management of the concerned airlines. The proposed SBM slacks suggest the possible areas of improvement for future planning and optimal operating input/output levels for the top management of the weakly efficient airlines.

This research is about the development of a dynamic programming model for solving fuzzy linear programming problems. Initially, fuzzy dynamic linear programming model FDLP is developed. This research revises the established dynamic programming model for solving linear programming problems in a crisp environment. The mentioned approach is upgraded to address the problem in an uncertain environment. Dynamic programming model can either be passing forward or backward. In the proposed approach backward dynamic programming approach is adopted to address the problem. It is then followed by implementing the proposed method on the education system of Pakistan. The education system of Pakistan comprises of the Primary, Middle, Secondary, and Tertiary education stages. The problem is to maximize the efficiency of the education system while achieving the targets with minimum usage of the constrained resources. Likewise the model tries to maximize the enrollment in the Primary, Middle, Secondary and Tertiary educational categories, subject to the total available resources in a fuzzy uncertain environment. The solution proposes that the enrollment can be increased by an amount 9997130, by increasing the enrollment in the Middle and Tertiary educational categories. Thus the proposed method contributes to increase the objective function value by 30%. Moreover, the proposed solutions violate none of the constraints. In other words, the problem of resources allocation in education system is efficiently managed to increase efficiency while remaining in the available constrained resources. The motivation behind using the dynamic programming methodology is that it always possesses a numerical solution, unlike the other approaches having no solution at certain times. The proposed fuzzy model takes into account uncertainty in the linear programming modeling process and is more robust, flexible and practicable.