An Airway Network Flow Assignment Approach Based on an Efficient Multiobjective Optimization Framework
Autor: | Xiangmin Guan, Xuejun Zhang, Yanbo Zhu, Dengfeng Sun, Jiaxing Lei |
---|---|
Jazyk: | angličtina |
Rok vydání: | 2015 |
Předmět: | |
Zdroj: | The Scientific World Journal, Vol 2015 (2015) |
Druh dokumentu: | article |
ISSN: | 2356-6140 1537-744X |
DOI: | 10.1155/2015/302615 |
Popis: | Considering reducing the airspace congestion and the flight delay simultaneously, this paper formulates the airway network flow assignment (ANFA) problem as a multiobjective optimization model and presents a new multiobjective optimization framework to solve it. Firstly, an effective multi-island parallel evolution algorithm with multiple evolution populations is employed to improve the optimization capability. Secondly, the nondominated sorting genetic algorithm II is applied for each population. In addition, a cooperative coevolution algorithm is adapted to divide the ANFA problem into several low-dimensional biobjective optimization problems which are easier to deal with. Finally, in order to maintain the diversity of solutions and to avoid prematurity, a dynamic adjustment operator based on solution congestion degree is specifically designed for the ANFA problem. Simulation results using the real traffic data from China air route network and daily flight plans demonstrate that the proposed approach can improve the solution quality effectively, showing superiority to the existing approaches such as the multiobjective genetic algorithm, the well-known multiobjective evolutionary algorithm based on decomposition, and a cooperative coevolution multiobjective algorithm as well as other parallel evolution algorithms with different migration topology. |
Databáze: | Directory of Open Access Journals |
Externí odkaz: |