In order to ensure the rational allocation and efficient utilization of airport apron resources,this study analyzes the safety operational rules in the apron allocation process.It considers constraints such as matching aircraft stand sizes,safety time intervals between the same apron and adjacent aprons.A multi-objective optimization model is developed to minimize the number of remote aprons and minimize the idle time of nearby aprons.A novel approach to apron allocation and optimization is proposed,combining the advantages of Genetic Algorithm(GA)and Particle Swarm Optimization(PSO)into a Genetic Particle Swarm Optimization(GAPSO)algorithm.The adaptive limitation on the particle velocity update is also improved.The simulation results demonstrate that the GAPSO algorithm performs better in terms of remote apron allocation and idle time of nearby aprons.It exhibits faster convergence speed and stronger global optimization ability,thereby enhancing the efficiency of aviation transportation and providing practical significance to airport management and apron resource allocation.
关键词
停机位分配/遗传粒子群算法/机位匹配/混合算法
Key words
Aircraft stands assignment/Genetic-particle swarm optimization/Aircraft position match/Hybrid algo-rithm
维普
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