[1]齐小刚,王亚洲,班利明,等.求解动态维修资源优化调度的多目标进化算法[J].智能系统学报,2023,18(2):305-313.[doi:10.11992/tis.202201001]
QI Xiaogang,WANG Yazhou,BAN Liming,et al.Multi-objective evolutionary algorithm for optimal scheduling of dynamic maintenance resources[J].CAAI Transactions on Intelligent Systems,2023,18(2):305-313.[doi:10.11992/tis.202201001]
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QI Xiaogang,WANG Yazhou,BAN Liming,et al.Multi-objective evolutionary algorithm for optimal scheduling of dynamic maintenance resources[J].CAAI Transactions on Intelligent Systems,2023,18(2):305-313.[doi:10.11992/tis.202201001]
求解动态维修资源优化调度的多目标进化算法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
18
期数:
2023年第2期
页码:
305-313
栏目:
学术论文—智能系统
出版日期:
2023-03-05
- Title:
- Multi-objective evolutionary algorithm for optimal scheduling of dynamic maintenance resources
- Keywords:
- maintenance resources; resources conflict; optimal scheduling; operational phase; supply center; multi-objective evolutionary algorithm; normal distribution crossover operator; coevolution
- 分类号:
- TP273
- 摘要:
- 为解决维修资源调度过程中出现的维修资源预测不准、资源冲突的问题，本文建立了不同作战阶段的多供应中心?多需求点的的动态维修资源优化调度模型，使得多个供应中心可以及时、高效地对需求点进行维修资源调度，减少了资源调度时间和每个需求点的维修资源不满足量。为了更好地求解提出的模型，本文提出了一种改进的多目标进化算法，在经典的多目标进化算法的基础上，使用正态分布交叉算子、全局探索增强型差分进化算子和自适应变异算子的协同进化策略，提高了算法的局部搜索能力和种群的多样性。仿真实验表明，本文提出的算法具有良好的收敛性和分布均匀性，并且具有较高的求解效率。
- Abstract:
- This paper establishes a dynamic maintenance resource optimization scheduling model of multi-supply centers and multi-demand points in different combat stages to solve the problems of inaccurate prediction and resource conflict in the process of maintenance resource scheduling. Therefore, multiple supply centers can timely and efficiently schedule maintenance resources at demand points. The model reduces the resource scheduling time and the unsatisfying amount of maintenance resources at each demand point. An improved multi-objective evolutionary algorithm is proposed in this paper to solve the proposed model effectively. The co-evolution strategy of the normal distribution crossover operator, global exploration enhanced differential evolution operator, and adaptive mutation operator is used to improve the local search capability and population diversity of the algorithm based on the classical MOEA/D algorithm. Simulation results show that the proposed algorithm has good convergence and distribution uniformity and has high solution efficiency.
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- 相似文献/References:
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[1]李猛,和伟辉,毛攀登,等.一种面向维修资源配送调度的遗传-烟花混合算法[J].智能系统学报,2022,17(1):88.[doi:10.11992/tis.202108027]
LI Meng,HE Weihui,MAO Pandeng,et al.A genetic-firework hybrid algorithm oriented to maintenance resource distribution scheduling[J].CAAI Transactions on Intelligent Systems,2022,17():88.[doi:10.11992/tis.202108027]
备注/Memo
收稿日期:2021-01-02。
基金项目:预研项目（80904010301）.
作者简介:齐小刚,教授,博士生导师,主要研究方向为复杂系统建模与数据处理、联合资源分配与系统仿真。主持完成国家自然科学基金项目、十三五预研项目、预研基金(重点项目)、省自然科学基金重点项目等30余项。获得军队和省部级科技进步二等奖1项、三等奖2项,省级教学成果奖一等奖2项。申请专利80余件(授权41件),登记软件著作权8件。发表学术论文150余篇;王亚洲,硕士研究生,主要研究方向为系统建模、资源调度优化;班利明,工程师,主要研究方向为装备维修保障优化
通讯作者:齐小刚. E-mail：xgqi@xidian.edu.cn
更新日期/Last Update:
1900-01-01