第3期 卢福强，等：模糊粒子群优化算法的第四方物流运输时间优化 ·483· travel schedule[J].Journal of systems engineering,2012, search on RBPF-SLAM algorithm based on quantum-be- 27(4):535-542 haved particle swarm optimization[J].CAAI transactions [9]薄桂华，黄敏.考虑拖期风险的第四方物流路径优化问 on intelligent systems,2018,13(5):829-835. 题模型与求解).复杂系统与复杂性科学，2018,15(3)： [19]GUANG He,LU Xiaoli.An improved QPSO algorithm 66-74 and its application in fuzzy portfolio model with con- BO Guihua,HUANG Min.Model and solution of routing straints[J].Soft computing,2021,25(12):7695-7706. optimization problem in the fourth party logistic eith tardi- [20]ZHAO Xingang,LIANG Ji,MENG Jin,et al.An im- ness risk[J].Complex systems and complexity science, proved quantum particle swarm optimization algorithm 2018.15(3):66-74 for environmental economic dispatch[J].Expert systems [10]王勇，赵骅，李勇.用禁忌算法求解第四方物流作业整 with applications,2020,152:113370. 合优化模型).系统工程学报，2006,21(2少143-149. 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[14]SOMPRACHA C,JAYAWEERA D,TRICOLI P. 作者简介： Particle swarm optimisation technique to improve energy 卢福强，副教授，博土，主要研究 efficiency of doubly-fed induction generators for wind 方向为智慧物流、供应链管理、项目风 turbines[J].The journal of engineering,2019,2019(18): 险管理。 4890-4895 [15]LAN Rushi,ZHU Yu,LU Huimin,et al.A two-phase learning-based swarm optimizer for large-scale optimiza- tion[J].IEEE transactions on cybernetics,2020, 2020:1-10 刘婷，本科生，主要研究方向为路 [16]ABDELBAR A M.ABDELSHAHID S.WUNSCH II D 径规划、优化算法。 C.Fuzzy PSO:A generation of particle swarm optimiza- tion[C]//Proceedings of International Joint Conference on Neural Networks.Montreal,Canada,2005:1086-1091. [17]CHEN Chen,XU Junqi,LIN Guobin,et al.Fuzzy adapt- ive control particle swarm optimization based on T-S fuzzy model of maglev vehicle suspension system[J]. 毕华玲，讲师，博士，主要研究方 Journal of mechanical science and technology,2020, 向为物流管理、项目管理，智能算法 34(1):43-54. 设计。 [18]伍永健，陈跃东，陈孟元.量子粒子群优化下的RBPF SLAM算法研究[J].智能系统学报，2018,13(5)： 829-835 WU Yongjian,CHEN Yuedong,CHEN Mengyuan.Re-travel schedule[J]. Journal of systems engineering, 2012, 27(4): 535–542. 薄桂华, 黄敏. 考虑拖期风险的第四方物流路径优化问 题模型与求解 [J]. 复杂系统与复杂性科学, 2018, 15(3): 66–74. BO Guihua, HUANG Min. Model and solution of routing optimization problem in the fourth party logistic eith tardi￾ness risk[J]. Complex systems and complexity science, 2018, 15(3): 66–74. [9] 王勇, 赵骅, 李勇. 用禁忌算法求解第四方物流作业整 合优化模型 [J]. 系统工程学报, 2006, 21(2): 143–149. WANG Yong, ZHAO Hua, LI Yong. Tabu search al￾gorithm for optimization model of integration of job of 4th party logistics[J]. Journal of systems engineering, 2006, 21(2): 143–149. [10] CUI Yan, HUANG Min, YANG Shengxiang, et al. Fourth party logistics routing problem model with fuzzy dura￾tion time and cost discount[J]. Knowledge-based systems, 2013, 50: 14–24. [11] 陈建清, 刘文煌, 李秀. 第四方物流中基于多维权的有 向图模型及算法 [J]. 工业工程与管理, 2003, 8(3): 45–48, 59. CHEN Jianqing, LIU Wenhuang, LI Xiu. The directed graph model with multi dimensions in the fourth party lo￾gistics and its algorithm[J]. Industrial engineering and management, 2003, 8(3): 45–48, 59. [12] KENNEDY J, EBERHART R C, SHI Y. Swarm intelli￾gence[M]. San Francisco: Morgan Kaufmann Publishers, 2001: 1−10. [13] SOMPRACHA C, JAYAWEERA D, TRICOLI P. Particle swarm optimisation technique to improve energy efficiency of doubly-fed induction generators for wind turbines[J]. The journal of engineering, 2019, 2019(18): 4890–4895. [14] LAN Rushi, ZHU Yu, LU Huimin, et al. A two-phase learning-based swarm optimizer for large-scale optimiza￾tion[J]. IEEE transactions on cybernetics, 2020, 2020:1−10. [15] ABDELBAR A M, ABDELSHAHID S, WUNSCH II D C. Fuzzy PSO: A generation of particle swarm optimiza￾tion[C]//Proceedings of International Joint Conference on Neural Networks. Montreal, Canada, 2005: 1086−1091. [16] CHEN Chen, XU Junqi, LIN Guobin, et al. Fuzzy adapt￾ive control particle swarm optimization based on T-S fuzzy model of maglev vehicle suspension system[J]. Journal of mechanical science and technology, 2020, 34(1): 43–54. [17] 伍永健, 陈跃东, 陈孟元. 量子粒子群优化下的 RBPF￾SLAM 算法研究 [J]. 智能系统学报, 2018, 13(5): 829–835. WU Yongjian, CHEN Yuedong, CHEN Mengyuan. Re- [18] search on RBPF-SLAM algorithm based on quantum-be￾haved particle swarm optimization[J]. CAAI transactions on intelligent systems, 2018, 13(5): 829–835. GUANG He, LU Xiaoli. An improved QPSO algorithm and its application in fuzzy portfolio model with con￾straints[J]. Soft computing, 2021, 25(12): 7695–7706. [19] ZHAO Xingang, LIANG Ji, MENG Jin, et al. An im￾proved quantum particle swarm optimization algorithm for environmental economic dispatch[J]. Expert systems with applications, 2020, 152: 113370. [20] CHENG Jiatang, XIONG Yan, AI Li. Fault diagnosis of wind turbine gearbox based on neighborhood QPSO and improved D-S evidence theory[J]. Recent advances in computer science and communications, 2020, 13(2): 248–255. [21] CAI Yujie, SUN Jun, WANG Jie, et al. Optimizing the codon usage of synthetic gene with QPSO algorithm[J]. Journal of theoretical biology, 2008, 254(1): 123–127. [22] XU Xinzheng, SHAN Dong, WANG Guanying, et al. Multimodal medical image fusion using PCNN optimized by the QPSO algorithm[J]. Applied soft computing, 2016, 46: 588–595. [23] LIN Sen, NAN Yurong. Optimization of rolling schedule in tandem cold mill based on QPSO algorithm[J]. Ad￾vanced materials research, 2010, 145: 165–170. [24] FAN Qiufeng, WANG Tao, CHEN Yang, et al. Design and application of interval Type-2 TSK fuzzy logic sys￾tem based on QPSO algorithm[J]. International journal of fuzzy systems, 2018, 20(3): 835–846. [25] 作者简介： 卢福强，副教授，博士，主要研究 方向为智慧物流、供应链管理、项目风 险管理。 刘婷，本科生，主要研究方向为路 径规划、优化算法。 毕华玲，讲师，博士，主要研究方 向为物流管理、项目管理，智能算法 设计。 第 3 期 卢福强，等：模糊粒子群优化算法的第四方物流运输时间优化 ·483·