Numerical Analysis Based on the Pressure Bulkhead of the Multi-objective Optimization

GA (genetic algorithm) approach suitable for solving multi-objective optimization problems is described and evaluated using a series of simple model problems. The GA optimization procedure converged to the global pare to front optimum for every case attempted, GA is able to find the global optimum results. This incentive extracting the data to the maximum extend possible to help designers to further improve the design or expedite the design process. Multi-objective optimization approach is flexible in application and extremely reliable, providing optimal results for all optimization problems attempted. Multi-objective optimal design is involve in performing a design optimization of pressure bulkheads calls for advanced techniques of numerical optimization. Multi-objective solution that overall improved the involved quantities, despite their inherent conflicting nature. The designer can choose which solution is the most convenient and accurate for the problems.