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

doi:10.3969/j.issn.1000-1565.2020.01.015

Abstract

Abstract: 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.

Key words: general aviation logistics, PSGA algorithm, AF-factor, storage optimization, performance optimization

CLC Number:

TP301

ZHANG Hao, AN Jingwen. Application of new PSGA algorithm in performance optimization of general aviation logistics system[J]. Journal of Hebei University (Natural Science Edition), 2020, 40(1): 104-112.

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