智能优化算法在供应链网络中的应用

张欣; 詹志辉

doi:10.11959/j.issn.2096-6652.202202

您当前的位置：

首页 >

文章列表页 >

智能优化算法在供应链网络中的应用

综述与展望 | 更新时间：2024-06-05

- 智能优化算法在供应链网络中的应用
- Application of intelligent optimization algorithms in supply chain network
- 智能科学与技术学报 2022年4卷第2期页码：174-183
- 作者机构：
  
  1. 江南大学人工智能与计算机学院，江苏无锡 214122
  2. 华南理工大学计算机科学与工程学院，广东广州 510006
- 作者简介：
  
  [ "张欣（1992– ），女，博士，江南大学人工智能与计算机学院讲师，主要研究方向为进化计算、群体智能及其在供应链网络和智能制造中的应用" ]
  [ "詹志辉（1984– ），男，博士，华南理工大学计算机科学与工程学院教授、博士生导师，主要研究方向为人工智能、进化计算、群体智能" ]
- 基金信息：
  
  国家重点研发计划基金资助项目;The National Key Research and Development Program of China(2019YFB2102102);国家自然科学基金资助项目;The National Natural Science Foundation of China(61822602);国家自然科学基金资助项目;The National Natural Science Foundation of China(61772207)
- DOI：10.11959/j.issn.2096-6652.202202
  中图分类号： TP301
- 网络出版日期：2022-06，
  
  纸质出版日期：2022-06-15
- 稿件说明：
移动端阅览
张欣, 詹志辉. 智能优化算法在供应链网络中的应用[J]. 智能科学与技术学报, 2022,4(2):174-183.

Xin ZHANG, Zhihui ZHAN. Application of intelligent optimization algorithms in supply chain network[J]. Chinese journal of intelligent science and technology, 2022, 4(2): 174-183.
张欣, 詹志辉. 智能优化算法在供应链网络中的应用[J]. 智能科学与技术学报, 2022,4(2):174-183. DOI： 10.11959/j.issn.2096-6652.202202.

Xin ZHANG, Zhihui ZHAN. Application of intelligent optimization algorithms in supply chain network[J]. Chinese journal of intelligent science and technology, 2022, 4(2): 174-183. DOI： 10.11959/j.issn.2096-6652.202202.

摘要

供应链网络通过需求和供应关系将各个成员连接起来，方便成员之间进行协调与合作，这在全球化竞争环境下显得尤为重要。对供应链网络结构进行优化改进能够缩小企业运营成本、提高企业收益，提升客户满意度，进而提高企业的竞争力。首先，通过分析供应链网络中的优化问题，从建模特征、决策变量类型和场景特征等不同角度对该问题进行分类，从而更清晰地介绍现有供应链网络研究工作中涉及的优化问题。然后，介绍并分析了遗传算法、蚁群优化算法和粒子群优化算法3种常用的智能优化算法及其在供应链网络优化问题中的应用情况。最后，对供应链网络优化问题的未来研究方向进行了展望。

Abstract

Supply chain network connects members by the relationship of demand and supply and facilitates the coordination and cooperation among these members

which is particularly important in the global competition environment.The optimization and improvement of supply chain network can reduce the operating cost of enterprises

increase the income of enterprises and the customer satisfaction

and then improve the competitiveness of enterprises.Firstly

the optimization problems of supply chain network were analyzed

and these problems from several different aspects were classified

such as modeling characteristics

decision variable types

and scene features

so as to introduce the optimization problems in the existing research of supply chain network more clearly.Then

three frequently used intelligent optimization algorithms and their applications in supply chain network optimization were introduced and analyzed

such as genetic algorithm

ant colony optimization algorithm and particle swarm optimization algorithm.Finally

the future research of the optimization of supply chain network was prospected.

关键词

Keywords

references

张相斌 , 林萍 , 张冲 . 供应链管理 [M ] . 北京 : 人民邮电出版社 , 2015 .

ZHANG X B , LIN P , ZHANG C . Supply chain management [M ] . Beijing : People’s Posts and Telecommunications Press , 2015 .

中华人民共和国国务院办公厅 . 国务院办公厅关于积极推进供应链创新与应用的指导意见 [J ] . 物流科技 , 2018 , 41 ( 2 ): 3 .

General Office of the State Council of the People’s Republic of China . Guidance of the General Office of the State Council on actively promoting the innovation and application of supply chain [J ] . Logistics Sci-tech , 2018 , 41 ( 2 ): 3 .

陈宝林 . 最优化理论与算法 [M ] . 北京 : 清华大学出版社 , 2005 .

CHEN B L . Optimization theory and algorithm [M ] . Beijing : Tsinghua University Press , 2005 .

肖晓伟 , 肖迪 , 林锦国 , 等 . 多目标优化问题的研究概述 [J ] . 计算机应用研究 , 2011 , 28 ( 3 ): 805 - 808 , 827 .

XIAO X W , XIAO D , LIN J G , et al . Overview on multi-objective optimization problem research [J ] . Application Research of Computers , 2011 , 28 ( 3 ): 805 - 808 , 827 .

HAGER W W , HEARN D W , PARDALOS P M . Large scale optimization [M ] .[S.l. ] : Springer Science and Business Media , 1994 .

唐嘉昌 , 姜潮 , 龙湘云 , 等 . 一种针对不确定性结构的区间鲁棒性优化方法 [J ] . 中国科学:技术科学 , 2019 , 49 ( 7 ): 787 - 802 .

TANG J C , JIANG C , LONG X Y , et al . An interval robust optimization method for uncertain structures [J ] . Scientia Sinica (Technologica) , 2019 , 49 ( 7 ): 787 - 802 .

李智勇 , 黄滔 , 陈少淼 , 等 . 约束优化进化算法综述 [J ] . 软件学报 , 2017 , 28 ( 6 ): 1529 - 1546 .

LI Z Y , HUANG T , CHEN S M , et al . Overview of constrained optimization evolutionary algorithms [J ] . Journal of Software , 2017 , 28 ( 6 ): 1529 - 1546 .

李蓬实 . 供应链网络模型研究综述 [J ] . 物流科技 , 2014 , 37 ( 4 ): 46 - 49 .

LI P S . Review of research on supply chain network model [J ] . Logistics Sci-Tech , 2014 , 37 ( 4 ): 46 - 49 .

胡招娣 , 黄承锋 , 梁喜 . 基于客户满意度的供应链优化模型研究 [J ] . 物流技术 , 2010 , 29 ( 15 ): 97 - 101 .

HU Z D , HUANG C F , LIANG X . Study on supply chain optimization model based on customer satisfaction [J ] . Logistics Technology , 2010 , 29 ( 15 ): 97 - 101 .

任宏涛 , 郭颖 , 周文戟 , 等 . 资源约束下绿色铝供应链网络设计多目标优化 [J ] . 系统工程理论与实践 , 2020 , 40 ( 8 ): 2090 - 2103 .

REN H T , GUO Y , ZHOU W J , et al . Multi-objective optimization of green aluminum supply chain network design under resource constraints [J ] . Systems Engineering-Theory ＆ Practice , 2020 , 40 ( 8 ): 2090 - 2103 .

汪金荣 , 邵竑湄 , 李舜 , 等 . 基于人工蚁群算法的电能表供应链路径最优化方法 [J ] . 电子设计工程 , 2020 , 28 ( 20 ): 62 - 65 , 70 .

WANG J R , SHAO H M , LI S , et al . The optimization method of supply chain path of electricity meter based on artificial ant colony algorithm [J ] . Electronic Design Engineering , 2020 , 28 ( 20 ): 62 - 65 , 70 .

ZHANG X , ZHAN Z H , ZHANG J . A fast efficient local search-based algorithm for multi-objective supply chain configuration problem [J ] . IEEE Access , 2020 , 8 : 62924 - 62931 .

姚建明 . 服务大规模定制模式下的供应链调度优化 [J ] . 运筹与管理 , 2015 , 24 ( 1 ): 10 - 18 .

YAO J M . Supply chain scheduling optimization in service mass customization [J ] . Operations Research and Management Science , 2015 , 24 ( 1 ): 10 - 18 .

江云剑 . 不确定条件下可持续生物燃料供应链鲁棒优化研究 [D ] . 南京:东南大学 , 2016 .

JIANG Y J . Robust optimization on sustainable biofuel supply chain under uncertainties [D ] . Nanjing:Southeast University , 2016 .

肖青 , 郑凯君 . 分割配送的生鲜产品库存-路径优化研究 [J ] . 包装工程 , 2020 , 41 ( 19 ): 140 - 147 .

XIAO Q , ZHENG K J . Inventory-routing optimization of fresh products by split delivery [J ] . Packaging Engineering , 2020 , 41 ( 19 ): 140 - 147 .

ZHANG X , ZHAN Z H , ZHANG J . Multiobjective direction driven local search for constrained supply chain configuration problem [C ] // Proceedings of the 2020 Genetic and Evolutionary Computation Conference . New York:ACM Press , 2020 : 299 - 300 .

MAHMOODI A . Stackelberg-Nash equilibrium of pricing and inventory decisions in duopoly supply chains using a nested evolutionary algorithm [J ] . Applied Soft Computing , 2020 , 86 : 105922 .

CHEN Y T , CAO Z C . An investigation on a closed-loop supply chain of product recycling using a multi-agent and priority based genetic algorithm approach [J ] . Mathematics , 2020 , 8 ( 6 ): 888 .

YUN Y , CHULUUNSUKH A , GEN M . Sustainable closed-loop supply chain design problem:a hybrid genetic algorithm approach [J ] . Mathematics , 2020 , 8 ( 1 ): 84 .

刘静 , 毛海军 , 胡思涛 . 电子商务下闭环供应链物流网络优化模型与算法 [J ] . 物流技术 , 2014 , 33 ( 15 ): 360 - 362 , 429 .

LIU J , MAO H J , HU S T . Model and algorithm in optimization of closed-loop supply chain logistics networks in E-commerce environment [J ] . Logistics Technology , 2014 , 33 ( 15 ): 360 - 362 , 429 .

陶帝豪 , 刘蓉 , 雷勇杰 , 等 . 基于绿色供应链的冷链物流配送路径优化 [J ] . 工业工程 , 2019 , 22 ( 2 ): 89 - 95 .

TAO D H , LIU R , LEI Y J , et al . A research on routing optimization of cold chain distribution based on green supply chain [J ] . Industrial Engineering Journal , 2019 , 22 ( 2 ): 89 - 95 .

龙静 , 张以彬 , 洪江涛 . 需求不确定下的供应柔性和库存优化模型 [J ] . 统计与决策 , 2011 ( 3 ): 34 - 36 .

LONG J , ZHANG Y B , HONG J T . Supply flexibility and inventory optimization model under demand uncertainty [J ] . Statistics and Decision , 2011 ( 3 ): 34 - 36 .

赵霞 , 曹宝明 , 窦建平 . 需求和原料价格不确定下农产品供应链网络鲁棒优化设计 [J ] . 管理工程学报 , 2017 , 31 ( 4 ): 178 - 185 .

ZHAO X , CAO B M , DOU J P . Robust optimal design of agri-food supply chain network under demand uncertainty and raw material price uncertainty [J ] . Journal of Industrial Engineering and Engineering Management , 2017 , 31 ( 4 ): 178 - 185 .

包子阳 . 智能优化算法及其MATLAB实例 [M ] . 北京 : 电子工业出版社 , 2016 .

BAO Z Y . Intelligent optimization algorithm and MATLAB example [M ] . Beijing : Electronic Industry Press , 2016 .

吴沛锋 . 智能优化算法及其应用 [D ] . 沈阳:东北大学 , 2012 .

WU P F . Intelligent optimization algorithms and their application [D ] . Shenyang:Northeastern University , 2012 .

SAMPSON J R . Adaptation in natural and artificial systems (John H.Holland) [J ] . SIAM Recview , 1976 , 18 ( 3 ): 529 - 530 .

张琛 , 詹志辉 . 遗传算法选择策略比较 [J ] . 计算机工程与设计 , 2009 , 30 ( 23 ): 5471 - 5474 , 5478 .

ZHANG C , ZHAN Z H . Comparisons of selection strategy in genetic algorithm [J ] . Computer Engineering and Design , 2009 , 30 ( 23 ): 5471 - 5474 , 5478 .

LIN J J , HUANG S C , JIAU M K . An evolutionary multiobjective carpool algorithm using set-based operator based on simulated binary crossover [J ] . IEEE Transactions on Cybernetics , 2019 , 49 ( 9 ): 3432 - 3442 .

戴卓 . 多周期多原料的供应链网络成本优化及其混合遗传算法 [J ] . 计算机应用研究 , 2014 , 31 ( 9 ): 2620 - 2624 .

DAI Z . Multi-material and multi-cycle cost optimization of supply chain network and hybrid genetic algorithm [J ] . Application Research of Computers , 2014 , 31 ( 9 ): 2620 - 2624 .

王建华 , 陈荣 . 基于多目标规划的钢铁供应链网络优化研究 [J ] . 物流技术 , 2015 , 34 ( 23 ): 142 - 146 .

WANG J H , CHEN R . Study on optimization of steel supply chain network based on multi-objective programming [J ] . Logistics Technology , 2015 , 34 ( 23 ): 142 - 146 .

DORIGO M , BIRATTARI M , STUTZLE T . Ant colony optimization [J ] . IEEE Computational Intelligence Magazine , 2006 , 1 ( 4 ): 28 - 39 .

孙靖 , 林杰 . 基于蚁群算法的大规模定制供应链调度优化研究 [J ] . 计算机应用 , 2006 , 26 ( 11 ): 2631 - 2638 .

SUN J , LIN J . Study of supply chain optimization scheduling in mass customization based on ant colony algorithm [J ] . Journal of Computer Applications , 2006 , 26 ( 11 ): 2631 - 2638 .

KENNEDY J , EBERHART R . Particle swarm optimization [J ] . 1995 International Conference on Neural Networks , 2011 , 4 ( 8 ): 1942 - 1948 .

张军 , 詹志辉 , 陈伟能 . 计算智能 [M ] . 北京 : 清华大学出版社 , 2009 .

ZHANG J , ZHAN Z H , CHEN W N , et al . Computational intelligence [M ] . Beijing : Tsinghua University Press , 2009 .

马斌 , 吴泽忠 . 基于改进的粒子群算法求解供应链网络均衡问题 [J ] . 运筹与管理 , 2020 , 29 ( 2 ): 122 - 128 .

MA B , WU Z Z . Research on supply chain network equilibrium model based on improved particle swarm optimization [J ] . Operations Research and Management Science , 2020 , 29 ( 2 ): 122 - 128 .

ZHANG X , DU K J , ZHAN Z H , et al . Cooperative coevolutionary bare-bones particle swarm optimization with function independent decomposition for large-scale supply chain network design with uncertainties [J ] . IEEE Transactions on Cybernetics , 2019 , 50 ( 10 ): 4454 - 4468 .

朱小龙 , 丁帅 , 朱卫东 , 等 . 基于 ε-约束与区间数线性规划的钢铁供应链能源优化模型 [J ] . 管理工程学报 , 2016 , 30 ( 2 ): 243 - 250 .

ZHU X L , DING S , ZHU W D , et al . An energy optimization model of iron and steel supply chain using ε-constraint method and interval linear programming approach [J ] . Journal of Industrial Engineering and Engineering Management , 2016 , 30 ( 2 ): 243 - 250 .

FATHOLLAHI-FARD A M , HAJIAGHAEI-KESHTELI M , TIAN G D , et al . An adaptive Lagrangian relaxation-based algorithm for a coordinated water supply and wastewater collection network design problem [J ] . Information Sciences , 2020 , 512 : 1335 - 1359 .

顾金伟 . 基于拉格朗日松弛的库存—路径问题优化 [D ] . 兰州:兰州交通大学 , 2017 .

GU J W . An optimization of inventory and routing problems based on Lagrangian relaxation [D ] . Lanzhou:Lanzhou Jiaotong University , 2017 .

王熹徽 , 李峰 , 梁樑 . 救灾物资供应网络解构及结构优化模型 [J ] . 中国管理科学 , 2017 , 25 ( 1 ): 139 - 150 .

WANG X H , LI F , LIANG L . The deconstruction of a relief material supply network and corresponding structure optimization model [J ] . Chinese Journal of Management Science , 2017 , 25 ( 1 ): 139 - 150 .

CAI X Y , MEI Z W , FAN Z , et al . A constrained decomposition approach with grids for evolutionary multiobjective optimization [J ] . IEEE Transactions on Evolutionary Computation , 2018 , 22 ( 4 ): 564 - 577 .

史城至 , 尚娟 . 突发事件下的供应链管理优化研究 [J ] . 现代商贸工业 , 2020 , 41 ( 32 ): 25 - 26 .

SHI C Z , SHANG J . Research on supply chain management optimization under emergencies [J ] . Modern Business Trade Industry , 2020 , 41 ( 32 ): 25 - 26 .

曾丽华 , 王健 . 考虑消费者风险规避行为的零售商渠道最优决策 [J ] . 统计与决策 , 2020 , 36 ( 4 ): 163 - 167 .

ZENG L H , WANG J . Retailer optimal channel decision of dual-channel supply chain considering consumer risk-averse behavior [J ] . Statistics ＆ Decision , 2020 , 36 ( 4 ): 163 - 167 .

LIU X F , ZHAN Z H , GU T L , et al . Neural network-based information transfer for dynamic optimization [J ] . IEEE Transactions on Neural Networks and Learning Systems , 2020 , 31 ( 5 ): 1557 - 1570 .

ZHAN Z H , LIU X F , ZHANG H X , et al . Cloudde:a heterogeneous differential evolution algorithm and its distributed cloud version [J ] . IEEE Transactions on Parallel and Distributed Systems , 2017 , 28 ( 3 ): 704 - 716 .

张翠竹 , 黄小原 . 柔性供应链优化模型及其应用 [C ] // 第6届全国青年管理科学与系统科学学术会议暨中国科协第 4 届青年学术年会卫星会议 . 出版地不详:出版者不详 , 2001 .

ZHANG C Z , HUANG X Y . Flexible supply chain optimization model and its application [C ] // Proceedings of the 6th National Youth Management Science and Systems Science Academic Conference and the 4th annual Youth Academic Conference Satellite Conference of China Association for Science and Technology .[S.l.:s.n. ] , 2001 .

许伟佳 . 鲁棒优化方法在供应链柔性承诺问题中的应用 [J ] . 物流工程与管理 , 2010 , 32 ( 8 ): 133 - 136 .

XU W J . Robust optimization applications to supply chain flexibility of commitments [J ] . Logistics Engineering and Management , 2010 , 32 ( 8 ): 133 - 136

ZHAO H , ZHAN Z H , LIN Y , et al . Local binary pattern-based adaptive differential evolution for multimodal optimization problems [J ] . IEEE Transactions on Cybernetics , 2019 , 50 ( 7 ): 3343 - 3357 .

WANG Z J , ZHAN Z H , LIN Y , et al . Automatic niching differential evolution with contour prediction approach for multimodal optimization problems [J ] . IEEE Transactions on Evolutionary Computation , 2020 , 24 ( 1 ): 114 - 128 .

HUANG S J , ZHONG J H , YU W J . Surrogate-assisted evolutionary framework with adaptive knowledge transfer for multi-task optimization [J ] . IEEE Transactions on Emerging Topics in Computing , 2019 .

TANG Z D , GONG M G , WU Y , et al . Regularized evolutionary multitask optimization:learning to intertask transfer in aligned subspace [J ] . IEEE Transactions on Evolutionary Computation , 2020 , 25 ( 2 ): 262 - 276 .

CHEN Z G , ZHAN Z H , WANG H , et al . Distributed individuals for multiple peaks:a novel differential evolution for multimodal optimization problems [J ] . IEEE Transactions on Evolutionary Computation , 2019 , 24 ( 4 ): 708 - 719 .

FENG L , ZHOU L , ZHONG J H , et al . Evolutionary multitasking via explicit autoencoding [J ] . IEEE Transactions on Cybernetics , 2019 , 49 ( 9 ): 3457 - 3470 .

浏览量

897

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

暂无数据