ZHOU Chi, ZHANG Xuejun, CAI Kaiquan, ZHANG Jun. Comprehensive Learning Multi-Objective Particle Swarm Optimizer for Crossing Waypoints Location in Air Route Network[J]. Chinese Journal of Electronics, 2011, 20(3): 533-538.
Citation: ZHOU Chi, ZHANG Xuejun, CAI Kaiquan, ZHANG Jun. Comprehensive Learning Multi-Objective Particle Swarm Optimizer for Crossing Waypoints Location in Air Route Network[J]. Chinese Journal of Electronics, 2011, 20(3): 533-538.

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

  • Received Date: 2010-08-01
  • Rev Recd Date: 2010-11-01
  • Publish Date: 2011-07-25
  • 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 multi-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.
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      沈阳化工大学材料科学与工程学院 沈阳 110142

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