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| Authors | Significance facts | Parametric study |
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| [11] | Evaluating the system’s performance using AHP | Variables: price; cost, security, reliability, service quality |
| [12] | Initiates to improve fuel economy and transport aircraft design configuration using the genetic algorithm (GA) | Variables: range, cruise speed, wing root chord, engine dry weight, and lift over drag ratio
Constraints: flight performance and design conditions |
| [13] | A comparison of different techniques using FANP & FAHP to obtain the suitable result to select the best one | Variables: price, cost, security, reliability, and service quality |
| [14] | Implementing multipoint optimization to improve the wide-body design to reduce fuel consumption and study through real-time flight mission | Variables: flight performance and design conditions |
| [15] | The implementation of MCDM in the Taiwan aviation sector such as airlines, airports, air traffic management | Variables: seat capacity, MTOW, range, cost, CASK, and comfort |
| [1] | Presented a unique approach to obtain the design variables using MCDM. Further, utilized the variable to find the wide-body aircraft market’s competiveness using Monte Carlo techniques | Variables: economics, comfort, environmental impact, and adaptability
Constraints: profitability, payload, emission, and flight performance |
| [16] | Selecting best suitable commercial aircraft using fuzzy APH & TOPSIS MCDM and checking the robustness of the solution | Seat capacity, MTOW, fuel consumption, LTO cycle, range, speed, price, fuel per seat, and DOC |
| [17] | Selection and evaluation process using entropy & WASPAS MCDM | Variables: seat capacity, MTOW, fuel consumption, LTO cycle, range, speed, DOC |
| [18] | Hybrid optimization approach was applied to overcome the aircraft weight and balance issues | Constraints: flight envelops and design conditions |
| [19] | By using nondominated sorting genetic algorithm II (NSGA-II), controlled the influence flight mission weightage | Constraints: design mission parameters of significance and portraits the effect of off-design mission weightings on the designs |
| [20] | Established a multiobjective optimization of the design parameters and compared it to two distinct optimized solutions such as (MLVM) more less-violations method (MOGA) multiobjective genetic algorithm | Variables: flight performance and design conditions |
| Proposed research | Implementing the concept of MCDM techniques to identify the baseline aircraft and compare it with the novel design. Optimization techniques are used on the variables in the constraints parameters to fulfil the objectives | Variables: design parameters with aerodynamic efficiency
Constraints: design mission parameters, of significance, and portraits the effect of off-design mission weightings on the designs |
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