多种群变异非线性动态粒子群算法求解机场登机口分配问题  

MULTI-GROUP MUTATION NONLINEAR DYNAMIC PARTICLE SWARM OPTIMIZATION FOR AIRPORT GATE ALLOCATION

作　　者：宋阿妮[1] 包贤哲 Song Ani;Bao Xianzhe(School of Electrical and Electronic Engineering,Hubei University of Technology,Wuhan 430068,Hubei,China)

机构地区：[1]湖北工业大学电气与电子工程学院,湖北武汉430068

出　　处：《计算机应用与软件》2023年第6期234-241,342,共9页Computer Applications and Software

基　　金：国家自然科学基金项目(61072130);湖北省自然科学基金项目(2014CFB581)。

摘　　要：针对机场登机口分配不均造成航班拥堵和资源浪费的问题,提出多种群变异非线性动态粒子群算法。该算法设立了多个粒子种群进化并变异,将每次变异迭代后的全局最优个体纳入一个优质种群,而后结合非线性策略和动态策略对优质群的进化公式做出了改进,优质种群通过此进化公式迭代得到问题的最优解。该算法明显加大了前期的搜索范围和种群多样性,并有效避免了算法陷入局部最优的早熟问题。为了证明改进策略的有效性,将改进策略分步加进传统PSO并用四种经典测试函数测试改进效果,结果证明了改进策略的有效性。最后将PSO、GA、FA以及提出新算法对机场登机口问题进行求解。结果证明,该算法的精确度相对于FA、GA、PSO提高了23.13%、14.94%、8.01%,对于机场登机口有着更好的适应性。Aiming at the problem of flight congestion and waste of resources caused by uneven distribution of airport gates,this paper proposes a multi-swarm mutation nonlinear dynamic particle swarm optimization.It set up multiple particle populations to evolve and mutate,and it incorporated the global optimal individuals after each iteration of mutation into a high-quality population.The evolution formula of the high-quality population was improved by combining nonlinear and dynamic strategies.The high-quality population obtained the optimal solution of the problem through the iteration of this evolution formula.The algorithm significantly increased the previous search range and population diversity,and it effectively avoided the premature problem of the algorithm falling into the local optimum.To prove the effectiveness of the improved strategy,the improved strategy was added to the traditional PSO step by step,and four classical test functions were used to test the improvement effect.The results proved the effectiveness of the improvement strategy.PSO,GA,FA and the proposed algorithm were used to solve the airport boarding gate problem.The results show that the accuracy of this algorithm is improved by 23.13%,14.94%,and 8.01%compared with FA,GA,and PSO,and it has better adaptability to airport gates.

关 键 词：机场登机口 粒子群算法 变异 多种群 非线性 动态 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]