Comprehensive Learning Multi-Objective Particle Swarm Optimizer for Crossing Waypoints Location in Air Route Network  

作　　者：ZHOU Chi ZHANG Xuejun CAI Kaiquan ZHANG Jun 

机构地区：[1]School of Electronics and Information Engineering, Beihang University, Beijing 100191, China [2]National Key Laboratory of CNS/ATM, Beijing 100191, China

出　　处：《Chinese Journal of Electronics》2011年第3期533-538,共6页电子学报（英文版）

基　　金：This work is supported by the National Basic Research Program of China （No.2011CB707000）, Foundation for Innovative Research Groups of the National Natural Science Foundation of China （No.60921001）, National Science Foundation for Distinguished Young Scholars of China （No.60625102）.

摘　　要：The optimization of national Air route network （ARN） has become an effective method to improve the safety and efficiency of air transportation. The Crossing waypoints location （CWL） problem is a crucial problem in the design of ARN. This paper formulates a multi-objective model for the CWL problem, and presents a Comprehensive learning multl-objective particle swarm optimizer （CLMOPSO） to minimize both airlines cost and flight conflicts. The application to redesign national ARN of China shows the proposed optimizer valid and effective by comparison with the conventional optimization algorithms. The application of the proposed methodology can also serve as a benchmark application as shown in the paper.

关 键 词：Air route network Crossing waypointslocation Multi-objective optimization. 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] TV213.9[自动化与计算机技术—计算机科学与技术]