基于改进粒子群算法的多约束随船备件配置优化  

Warship Spare Parts Allotment Optimization Method Under Multiple Constraints Based on Improved Particle Swarm Optimization Algorithm

作　　者：张蓉 刘成龙 邵红伟[1] 周宏飞[1] 张璟[1] ZHANG Rong;LIU Chenglong;SHAO Hongwei;ZHOU Hongfei;ZHANG Jing(China Ship Development and Design Center,Wuhan 430064;No.93119 Troops of PLA,Jiuquan 735018)

机构地区：[1]中国舰船研究设计中心,武汉430064 [2]中国人民解放军93119部队,酒泉735018

出　　处：《舰船电子工程》2023年第11期102-108,共7页Ship Electronic Engineering

摘　　要：为合理配置船舶随船备件,构建了多约束条件下的备件配置优化模型,提出了一种改进的粒子群算法对模型求解。首先,以备件费用、存储空间、重量为约束条件,以最大化系统备件保障概率为优化目标,通过构造含罚函数的适应度函数,将多约束最优化问题转化为无约束最优化问题;其次,设计了一种基于模拟退火改进的粒子群算法求解优化模型;最后,通过开展仿真实验,证明了该方法在求解随船备件配置优化问题的有效性和优越性。In order to make the warship spare parts configuration more reasonable,the optimal configuration model of warship spare parts under multiple constraints is constructed,and an improved particle swarm optimization algorithm based on simulated an⁃nealing algorithm is proposed.Firstly,an optimization model with the cost,storage space and weight of spare parts as constraints and the maximization of system spare parts guarantee probability as the optimization objective is constructed,and the multiple con⁃straints optimization model is transformed into an unconstrained optimization model by constructing a penalty function,which reduc⁃es the requirements for the solution algorithm.Secondly,an improved particle swarm optimization algorithm based on simulated an⁃nealing algorithm is designed to solve the optimization model.Finally,simulation results show that the proposed method is effective and superior in solving the optimization problem of warship spare parts configuration.

关 键 词：随船备件 多约束 系统备件保障概率 模拟退火算法 粒子群算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]