基于交叉效率排序多目标进化算法的备件供应优化

doi:10.3969/j.issn.1000-1093.2020.11.022

兵工学报 ›› 2020, Vol. 41 ›› Issue (11): 2338-2346.doi: 10.3969/j.issn.1000-1093.2020.11.022

基于交叉效率排序多目标进化算法的备件供应优化

王亚东¹，石全¹，尤志锋¹，王芳¹，夏伟^1，2

（1.陆军工程大学石家庄校区装备指挥与管理系, 河北石家庄 050003；2.陆军步兵学院石家庄校区机械化步兵系, 河北石家庄 050083）

上线日期:2020-12-04
通讯作者: 石全(1966—)，男，教授，博士生导师 E-mail:junshiyc@163.com
作者简介:王亚东(1992—)，男，博士研究生。E-mail: xwzj0003@163.com
基金资助:
武器装备 “十三五”预先研究共用技术项目(41404050501)；军内科研重点项目(KYSZJWJK1742)

Spare Parts Supply Optimization and Decision-making Based on Cross-efficiency Multi-objective Sorting Evolutionary Algorithm

WANG Yadong¹， SHI Quan¹， YOU Zhifeng¹， WANG Fang¹， XIA Wei^1，2

(1.Department of Equipment Command and Management, Shijiazhuang Campus, Army Engineering University, Shijiazhuang 050003, Hebei， China; 2.Department of Mechanized Infantry, Shijiazhuang Campus, Army Infantry College, Shijiazhuang 050083, Hebei, China)

Online:2020-12-04

摘要/Abstract

摘要： 为了对备件供应网络进行优化并制定最优供应方案，以缩短总供应时间、减少供应成本和降低中断风险为目标，以备件满足度、库存容量等为约束建立了多目标优化模型。基于交叉效率排序多目标进化算法求得模型的非支配解集，同时决策出最优解。优化过程中采用改进数据包络分析计算各最优解的二次目标交叉效率，指导算法朝最优效率个体收敛，对求得的非支配解进行排序从而选择出最优方案。算例表明：通过交叉效率排序多目标进化算法优化得到了13个互不支配的备件供应方案，且确定了交叉效率为0.927 8的方案为最优方案；新算法优于未采用排序和采用自评效率排序的多目标进化算法。

关键词: 备件供应, 多目标优化, 进化计算, 数据包络分析, 交叉效率, 排序

Abstract: A multi-objective optimization model is established with the constraints of spare parts satisfaction, lead time and inventory capacity for the shortest total supply time, the lowest risk and the minimum cost. The proposed model is used to optimize the spare parts supply and make an optimal supply scheme. The set of non-dominant solutions are obtained by using the proposed secondary goal cross-efficiency sort multi-objective evolutionary algorithm (SGCES-MOEA). During optimization process, the improved data envelopment analysis (DEA) is used to calculate the cross-efficiencies of the non-dominant solutions. On the one hand, the algorithm is guided to converge to the optimal efficiency individuals. On the other hand, the non-dominant solutions are sorted to select an optimal one. The example shows that 13 non-dominate spare parts supply schemes are obtained by using SGCES-MOEA algorithm, and the scheme with cross-efficiency of 0.927 8 is determined as the optimal scheme. The new algorithm is superior to the multi-objective evolutionary algorithm without efficiency sorting strategy and that with self-evaluation efficiency sorting strategy.

Key words: sparepartssupply, multi-objectiveoptimization, evolutionarycomputation, dataenvelop-mentanalysis, cross-efficiency, sorting

中图分类号:

王亚东，石全，尤志锋，王芳，夏伟. 基于交叉效率排序多目标进化算法的备件供应优化[J]. 兵工学报, 2020, 41(11): 2338-2346.

WANG Yadong， SHI Quan， YOU Zhifeng， WANG Fang， XIA Wei. Spare Parts Supply Optimization and Decision-making Based on Cross-efficiency Multi-objective Sorting Evolutionary Algorithm[J]. Acta Armamentarii, 2020, 41(11): 2338-2346.

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基于交叉效率排序多目标进化算法的备件供应优化

Spare Parts Supply Optimization and Decision-making Based on Cross-efficiency Multi-objective Sorting Evolutionary Algorithm

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