Cooperative co-evolution with weighted random grouping for large-scale Crossing Waypoints Locating in Air Route Network

Mingming Xiao*, Jun Zhang, Kaiquan Cai, Xianbin Cao, Tang Ke

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Citations (Scopus)

Abstract

The large-scale Crossing Waypoints Location Problem (CWLP) is a crucial problem in the design of Air Route Network (ARN). CWLP is fully non-separable and non-differentiable, and thus traditional algorithms can hardly deal with it. This paper proposes an algorithm named Cooperative Co-evolution with Weighted Random Grouping (CCWR) to tackle it. CCWR employs the weighted random (WR) grouping strategy, which is specifically designed for CWLP, to divide the large-scale Crossing Waypoints (CWs) into small sub-groups and an Evolutionary Algorithm (EA) to solve the smaller scale CWs location problem in each sub-group. Experiments on the database of the ARN in China have been carried out to evaluate the performance of CCWR. The results showed that CCWR is superior to a number of state-of-the-art algorithms, and the advanced performance of CCWR is mainly due to the WR grouping strategy.

Original languageEnglish
Title of host publicationProceedings - 2011 23rd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2011
Pages215-222
Number of pages8
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event23rd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2011 - Boca Raton, FL, United States
Duration: 7 Nov 20119 Nov 2011

Publication series

NameProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
ISSN (Print)1082-3409

Conference

Conference23rd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2011
Country/TerritoryUnited States
CityBoca Raton, FL
Period7/11/119/11/11

Keywords

  • Air Route Network
  • Cooperative Co-evolution
  • Crossing Waypoints Location

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