Particle swarm optimization with a mutation operator for solving the preventive aircraft maintenance routing problem

被引：0
|
作者：
Sarhani, Malek [1 ]
Ezzinbi, Omar [1 ]
El Afia, Abdellatif [1 ]
Benadada, Youssef [1 ]
机构：
[1] Mohammed V Univ, ENSIAS, Rabat, Morocco
来源：
PROCEEDINGS OF THE 3RD IEEE INTERNATIONAL CONFERENCE ON LOGISTICS OPERATIONS MANAGEMENT (GOL'16) | 2016年
关键词：
Aircraft maintenance routing; Unscheduled maintenance; Particle Swarm Optimization; Mutation operator; Constrained optimization;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Aircraft Maintenance Routing (AMR) is one of the major optimization problems in the airline industry. In this study, we present a mathematical formulation for the daily AMR problem which aims to minimize the risk of both scheduled and non-scheduled maintenance costs. Exact methods may fail to deal with such problems. Our contribution is then to examine the use of an improved particle swarm optimization (PSO) algorithm by a uniform mutation operator for solving this probabilistic problem. Computational results show that our hybrid approach gives competitive results comparing to the native binary PSO.
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页数：6
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