文献类型：期刊文献

英文题名：Hybridized encoding for evolutionary multi-objective optimization of air traffic network flow: A case study on China

作者：Xiao, Mingming[1];Cai, Kaiquan[2];Abbass, Hussein A.[3]

通讯作者：Xiao, MM[1]

机构：[1]Beijing Union Univ, Smart City Coll, North 4th Ring East Rd, Beijing 100101, Peoples R China;[2]Beihang Univ, Sch Elect & Informat Engn, Beijing, Peoples R China;[3]Univ New South Wales, Sch Engn & Informat Technol, Sydney, NSW, Australia

第一机构：北京联合大学继续教育学院

通讯机构：[1]corresponding author), Beijing Union Univ, Smart City Coll, North 4th Ring East Rd, Beijing 100101, Peoples R China.|[1141733]北京联合大学继续教育学院;[11417]北京联合大学;

年份：2018

卷号：115

起止页码：35-55

外文期刊名：TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW

收录：;EI(收录号：20233214514299);Scopus(收录号：2-s2.0-85046367255);WOS:【SSCI(收录号:WOS:000438832100003)，SCI-EXPANDED(收录号:WOS:000438832100003)】；

基金：This work was supported by "New Start" Academic Research Projects of Beijing Union University (No. Zk10201705), National Science Foundation for Young Scientists of China (No. 61401011).

语种：英文

外文关键词：Air traffic management; Flow optimization; Memetic computing; Interdependent optimization

摘要：This paper presents a novel hybridized indirect and direct encoding (HybrID) genetic algorithm for solving air traffic network flow optimization problems. A heuristic, which uses the Dijkstra algorithm for generating different types of shortest paths on a graph while controlling the weights on each arc, is proposed for selecting optimal flight routes based on current air traffic. A novel HybrID chromosome representation is employed along with the proposed heuristic and a genetic algorithm for optimization. Experiments on synthetic problems and real data of the Chinese airspace show the proposed method outperforms the direct encoding method on efficiency and efficacy metrics.