姚拓中
YAO Tuozhong

• 1:宁波工程学院

摘要(Abstract)：

传统电力供应链存在智能化协同程度低和节点企业合作效率低等问题，影响了供应链节点企业的利润。为此，在区块链技术基础上搭建基于供应商和经销商的二级供应链博弈模型，提出一种利用粒子群优化和蚁群算法指导供应链节点企业通过博弈作出最优选择的竞争策略。先通过粒子群优化算法估计供应商的利润函数并以此为基础制定初始的竞争博弈策略，进而采用基于深度神经网络优化的蚁群算法实现供应商和经销商的最优业务匹配。最后，通过实验验证了所提方法对于提高电力供应链企业竞争力的有效性。
The traditional power system supply chain is inferior in intelligent coordination and is inefficient in cooperation between nodal enterprises,of which the profits are held up. Therefore,a two-level supply chain game model based on suppliers and dealers is built with the help of blockchain technology. This paper proposes a method that combines particle swarm optimization and ant colony algorithm to guide the supply chain nodal enterprises to select the optimal competition strategy through gaming. It estimates the supplier's profit function through particle swarm optimization algorithm and thus formulates the initial competition game strategy. Besides,the ant colony algorithm based on deep neural network optimization is used to match suppliers and dealers perfectly. Finally,experiments verify the effectiveness of this method in improving the competitiveness of power supply chain enterprises.

关键词(KeyWords)： 供应链博弈;粒子群优化;蚁群算法;深度学习
supply chain gaming;particle swarm optimization;ant colony algorithm;deep learning

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金面上项目（62071267）;; 浙江大学工业控制国家重点实验室开放课题（ICT20047）;; 国网浙江省电力有限公司科技项目（5211WF20000C）

作者(Author): 姚拓中
YAO Tuozhong

DOI: 10.19585/j.zjdl.202209010

参考文献(References)：

• [1]李季芳.供应链节点企业竞争合作博弈分析[J].理论学刊，2014(4):65-69.
• [2]孔祥西，程钧谟，张金山.供应链企业间知识共享的合作响应博弈分析[J].山东理工大学学报（自然科学版），2016,30(4):44-48.
• [3]张路.博弈视角下区块链驱动供应链金融创新研究[J].经济问题，2019(4):48-54.
• [4] LIU W H,WANG Y J.Quality control game model in logistics service supply chain based on different combinations of risk attitude[J]. International Journal of Production Economics,2015(161):181-191.
• [5]关越.基于区块链的供应链信息协同管理研究[D].秦皇岛：燕山大学，2018.
• [6]万强强.基于区块链的电子供应链信息管理机制研究[D].太原：中北大学，2020.
• [7]张志，李军祥，张栋梁.基于联盟区块链的供应链信息协同博弈研究[J].计算机应用研究，2021,38(5):1314-1319.
• [8] DAI H Y,LI J B,YAN N N,et al.Bullwhip effect and supply chain costs with low and high quality information on inventory shrinkage[J]. European Journal of Operational Research,2016,250(2):457-469.
• [9] TALEIZADEH A A, NOORI-DARYAN M,CáRDENAS-BARRóN L E.Joint optimization of price,replenishment frequency,replenishment cycle and production rate in vendor managed inventory system with deteriorating items[J]. International Journal of Production Economics,2015(159):285-295.
• [10] ESMAEILI M,SEDEHZADE S. Designing a hub location and pricing network in a competitive environment[J].Journal of Industrial and Management Optimization,2020,16(2):653-667.
• [11]侯文捷，武鸿鹏，高峰亭，等.基于区块链智能合约的电力供应链利益分配研究[J].信阳师范学院学报（自然科学版），2020,33(1):144-148.
• [12]李敏法.电力供应链管理的采购策略探微[J].农村经济与科技，2018,29(20):205-206.
• [13]张轶堃.基于智能算法和Multi-Agent的电力供应链网络协同的研究[D].长春：吉林大学，2016.
• [14] PANG S C,MA T M,LIU T.An improved ant colony optimization with optimal search library for solving the traveling salesman problem[J]. Journal of Computational and Theoretical Nanoscience,2015,12(7):1440-1444.
• [15]杜伟佳.区块链环境下供应链节点企业博弈研究[D].秦皇岛：燕山大学，2020.
• [16] PRATES M,AVELAR P H C,LEMOS H,et al.Learning to solve NP-complete problems:A graph neural network for decision TSP[J].Proceedings of the AAAI Conference on Artificial Intelligence,2019,33:4731-4738.
• [17] NAZARI M,OROOJLOOY A,SNYDER L,et al.Reinforcement learning for solving the vehicle routing problem[J].Proceedings of Advances in Neural Information Processing Systems(NeurIPS),2018:9839-9849.
• [18]王原，陈名，邢立宁，等.用于求解旅行商问题的深度智慧型蚁群优化算法[J].计算机研究与发展，2021,58(8):1586-1598.
• [19]刘晓东，王璇.能源互联网技术产业链融合创新机制与对策研究[J].电力电容器与无功补偿，2021,42(6):260-267.
• [20]祁兵，赵燕玲，杨帆，等.区块链在需求响应中的关键技术及现状分析[J].内蒙古电力技术，2021,39(4):22-26.
• [21]王灏，宝音，丁畅.基于区块链技术的电力市场绿色证书交易机制研究[J].内蒙古电力技术，2021,39(4):47-50.
• [22]杨亭，雷霆.基于主从区块链技术的区域能源交易架构[J].四川电力技术，2021,44(1):89-94.
• [23]陈梦恺，付保川，吴征天，等.微电网中博弈问题及其发展动向[J].电器与能效管理技术，2021(1):1-8.
• [24]佘佐超，李喆，刘浩宇.基于区块链的电力数据共享研究初探[J].四川电力技术，2020,43(6):31-38.
• [25]赵升，徐小舒，吴征天.区块链技术在分布式能源交易领域的创新应用[J].电器与能效管理技术，2020(11):1-10.