新型PSGA算法在通航物流系统效能优化中的应用

为提升对时间效率要求较高的通航物流系统整体运行效能,设计和提出了一种新型变种群极搜索遗传算法(PSGA).通过在算法逻辑结构上对传统遗传算法(GA)进行重新设计,同时创新性地设计和引入一种适应度调和因子,使PSGA的算法效率较传统GA算法有了明显提升.经过2个不同复杂度的函数寻优测试显示,PSGA在效率上分别高出GA35.35%和43.50%;最后,通过实际案例应用表明,PSGA的收敛效率高出GA25代,优化精度高出GA1.46.测试与应用结果说明,PSGA算法在通航物流系统效能优化中具有较好的有效性和适用性.

Application of new PSGA algorithm in performance optimization of general aviation logistics system

In order to enhance the performance of the general aviation logistics system which requires mach higher time efficiency, this paper designs and proposes a new variable population and pole search genetic algorithm(PSGA). By redesigning the traditional genetic algorithm(GA)in the logical structure, and innovatively designing and introducing a fitness factor, the algorithm efficiency of PSGA is made higher than that of traditional GA.Through two function optimization tests with different complexity,the efficiency of PSGA is made higher than that of GA for 35.35% and 43.50%. Finally, the practical application shows that the convergence efficiency of PSGA is higher than that of GA for 25 generations and the optimization accuracy is higher than that of GA for 1.46. The tests and application results show that PSGA algorithm has better effectiveness and applicability in the performance optimization of general aviation logistics system.