摘要
针对舰船海上执行任务期间随舰特装器材的保障问题,研究了特装器材的多目标优化配置方法。结合舰船特装器材保障的实际特点,以器材的体积、质量、费用为约束条件,以保障概率和利用率为优化目标,建立多目标多约束特装器材优化配置模型,并改进多目标粒子群算法,保证全局范围粒子多样性,避免算法过快收敛,以求得全局最优解。通过实例对比改进粒子群算法与标准算法的计算结果,分析不同指标权重比组合下的最优配置方案、不同约束条件下的多目标变化趋势,证明了改进粒子群算法的稳定性和多目标优化模型的实用性。
This paper studies the multi-objective optimization configuration of special equipment materials on warships during the mission at sea. Considering the configuration characteristics of special equipment materials on warships, we establish a multiobjective and multi-constraint model with the fill rate and utilization rate as the optimization target, and volume, mass, and cost as the constraints. The multi-objective Particle Swarm Optimization（PSO） algorithm is designed and improved, guaranteeing diversity of particles at the global scope and avoiding excessively fast convergence, to obtain globally optimal solution. We further compare the calculation results between the improved algorithm and standard algorithm, analyzing the optimal configuration under different weight ratio and tendencies under different constraints. The results demonstrate the stability of the improved algorithm and practicability of the multi-objective model.
出处
《科技导报》
CAS
CSCD
北大核心
2015年第19期96-101,共6页
Science & Technology Review
基金
中国航天科技集团一院预研项目(2014-KYFX-0071)
关键词
舰船特装器材
优化配置
保障概率
多目标优化
special equipment materials
optimization configuration
fill rate
multi-objective optimization
