Research on Multi-objective Optimization Model of Power Storage Materials Based on NSGA-II Algorithm
Abstract Aiming at the problems of slow convergence speed and low precision probability of multi-objective optimization of energy storage materials, a multi-objective optimization model of energy storage materials based on NSGA-II algorithm was proposed. The association rule set of storage materials...
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Springer
2024-04-01
|
Series: | International Journal of Computational Intelligence Systems |
Subjects: | |
Online Access: | https://doi.org/10.1007/s44196-024-00454-3 |
_version_ | 1797219574392815616 |
---|---|
author | Zixi Hu Shuang Liu Fan Yang Xiaodong Geng Xiaodi Huo Jia Liu |
author_facet | Zixi Hu Shuang Liu Fan Yang Xiaodong Geng Xiaodi Huo Jia Liu |
author_sort | Zixi Hu |
collection | DOAJ |
description | Abstract Aiming at the problems of slow convergence speed and low precision probability of multi-objective optimization of energy storage materials, a multi-objective optimization model of energy storage materials based on NSGA-II algorithm was proposed. The association rule set of storage materials in the joint supply chain operation performance management system is extracted, and the rough vector feature distribution set multi-objective optimization method is used to decompose and optimize the characteristics of storage materials in the joint supply chain operation performance management system. Using NSGA-II optimization analysis method, this paper summarizes the power storage materials under the joint supply chain operation performance management system, and summarizes three kinds of inventory control: periodic inventory, inventory coding, and computerized inventory. Combined with the positive regression learning method of organizational operational performance, the multi-objective optimization decision of electric storage materials under the joint supply chain operational performance management system is realized. The simulation results show that under the joint supply chain operation performance management system, the proposed method reaches the optimal convergence after 65 iterations, the convergence speed is fast, and the accuracy probability reaches 1.000 after 80 iterations, which solves the problems of slow convergence speed and low accuracy probability, and has a good scheduling ability of energy storage materials. |
first_indexed | 2024-04-24T12:35:49Z |
format | Article |
id | doaj.art-15cbe312057b49e494cf451e3567bc93 |
institution | Directory Open Access Journal |
issn | 1875-6883 |
language | English |
last_indexed | 2024-04-24T12:35:49Z |
publishDate | 2024-04-01 |
publisher | Springer |
record_format | Article |
series | International Journal of Computational Intelligence Systems |
spelling | doaj.art-15cbe312057b49e494cf451e3567bc932024-04-07T11:29:58ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832024-04-0117111310.1007/s44196-024-00454-3Research on Multi-objective Optimization Model of Power Storage Materials Based on NSGA-II AlgorithmZixi Hu0Shuang Liu1Fan Yang2Xiaodong Geng3Xiaodi Huo4Jia Liu5State Grid Hebei Electric Power Co., Ltd., Shijiazhuang Power Supply BranchState Grid Hebei Electric Power Co., Ltd., Shijiazhuang Power Supply BranchState Grid Hebei Electric Power Co., Ltd.State Grid Hebei Electric Power Co., Ltd., Shijiazhuang Power Supply BranchState Grid Shijiazhuang Luancheng District Electric Power Supply CompanyState Grid Pingshan Electric Power Supply CompanyAbstract Aiming at the problems of slow convergence speed and low precision probability of multi-objective optimization of energy storage materials, a multi-objective optimization model of energy storage materials based on NSGA-II algorithm was proposed. The association rule set of storage materials in the joint supply chain operation performance management system is extracted, and the rough vector feature distribution set multi-objective optimization method is used to decompose and optimize the characteristics of storage materials in the joint supply chain operation performance management system. Using NSGA-II optimization analysis method, this paper summarizes the power storage materials under the joint supply chain operation performance management system, and summarizes three kinds of inventory control: periodic inventory, inventory coding, and computerized inventory. Combined with the positive regression learning method of organizational operational performance, the multi-objective optimization decision of electric storage materials under the joint supply chain operational performance management system is realized. The simulation results show that under the joint supply chain operation performance management system, the proposed method reaches the optimal convergence after 65 iterations, the convergence speed is fast, and the accuracy probability reaches 1.000 after 80 iterations, which solves the problems of slow convergence speed and low accuracy probability, and has a good scheduling ability of energy storage materials.https://doi.org/10.1007/s44196-024-00454-3NSGA-II algorithmElectric power storage materialsMulti-objective optimizationRough vectorJoint supply chainOperational performance management |
spellingShingle | Zixi Hu Shuang Liu Fan Yang Xiaodong Geng Xiaodi Huo Jia Liu Research on Multi-objective Optimization Model of Power Storage Materials Based on NSGA-II Algorithm International Journal of Computational Intelligence Systems NSGA-II algorithm Electric power storage materials Multi-objective optimization Rough vector Joint supply chain Operational performance management |
title | Research on Multi-objective Optimization Model of Power Storage Materials Based on NSGA-II Algorithm |
title_full | Research on Multi-objective Optimization Model of Power Storage Materials Based on NSGA-II Algorithm |
title_fullStr | Research on Multi-objective Optimization Model of Power Storage Materials Based on NSGA-II Algorithm |
title_full_unstemmed | Research on Multi-objective Optimization Model of Power Storage Materials Based on NSGA-II Algorithm |
title_short | Research on Multi-objective Optimization Model of Power Storage Materials Based on NSGA-II Algorithm |
title_sort | research on multi objective optimization model of power storage materials based on nsga ii algorithm |
topic | NSGA-II algorithm Electric power storage materials Multi-objective optimization Rough vector Joint supply chain Operational performance management |
url | https://doi.org/10.1007/s44196-024-00454-3 |
work_keys_str_mv | AT zixihu researchonmultiobjectiveoptimizationmodelofpowerstoragematerialsbasedonnsgaiialgorithm AT shuangliu researchonmultiobjectiveoptimizationmodelofpowerstoragematerialsbasedonnsgaiialgorithm AT fanyang researchonmultiobjectiveoptimizationmodelofpowerstoragematerialsbasedonnsgaiialgorithm AT xiaodonggeng researchonmultiobjectiveoptimizationmodelofpowerstoragematerialsbasedonnsgaiialgorithm AT xiaodihuo researchonmultiobjectiveoptimizationmodelofpowerstoragematerialsbasedonnsgaiialgorithm AT jialiu researchonmultiobjectiveoptimizationmodelofpowerstoragematerialsbasedonnsgaiialgorithm |