Corrigendum to “Optimal design methods for a digital human-computer interface based on human reliability in a nuclear power plant: Part 2: The optimization design method for component quantity” [Ann. Nucl. Energy 106 (2017) 247–255]
作者：
Jiang, Jianjun* ;Zhang, Li;Wang, Yiqun;Xie, Tian;Wu, Daqing;...
期刊：
Annals of Nuclear Energy ,2018年111:715 ISSN：0306-4549
通讯作者：
Jiang, Jianjun
作者机构：
[Jiang, Jianjun; Wang, Yiqun; Zhang, Mengjia; Zhang, Li; Xie, Tian] Univ South China, Human Factors Inst, Sch Management, Hengyang 421001, Hunan, Peoples R China.;[Jiang, Jianjun; Zhang, Li] Hunan Inst Technol, Sch Safety & Environm Engn, Hengyang 421002, Hunan, Peoples R China.;[Li, Min; Wu, Daqing] Univ South China, Sch Comp Sci & Technol, Hengyang 421001, Hunan, Peoples R China.;[Peng, Yuyuan] South China Univ Technol, Sch Comp Engn, Guangzhou Coll, Guangzhou 510830, Guangdong, Peoples R China.;[Peng, Jie] GuangDong Univ Finance & Econ, Informat Sci Coll, Guangzhou 510320, Guangdong, Peoples R China.
通讯机构：
[Jiang, Jianjun] U;Univ South China, Human Factors Inst, Sch Management, Hengyang 421001, Hunan, Peoples R China.
摘要：
The author regrets that the order of author list and affiliations of the above paper were incorrectly produced in the printed issue. The correct order of author list and affiliations appears above. The authors would like to apologise for any inconvenience caused. © 2017
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英文
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Minimization of Logistics Cost and Carbon Emissions Based on Quantum Particle Swarm Optimization
作者：
Wu, Daqing* ;Huo, Jiazhen;Zhang, Gefu;Zhang, Weihua
期刊：
Sustainability ,2018年10(10):3791 ISSN：2071-1050
通讯作者：
Wu, Daqing
作者机构：
[Zhang, Weihua; Wu, Daqing] Shanghai Ocean Univ, Coll Econ & Management, Shanghai 201306, Peoples R China.;[Wu, Daqing] Univ South China, Comp Sci & Technol Inst, Hengyang 421001, Peoples R China.;[Huo, Jiazhen; Wu, Daqing] Tongji Univ, Sch Econ & Management, Shanghai 20092, Peoples R China.;[Zhang, Gefu] Univ South China, Coll Econ & Management, Hengyang 421001, Peoples R China.
通讯机构：
[Wu, Daqing] S;[Wu, Daqing] U;[Wu, Daqing] T;Shanghai Ocean Univ, Coll Econ & Management, Shanghai 201306, Peoples R China.;Univ South China, Comp Sci & Technol Inst, Hengyang 421001, Peoples R China.
关键词：
logistics;carbon emissions;green supply chain;quantum-particle swarm optimization
摘要：
This paper aims to simultaneously minimize logistics costs and carbon emissions. For this purpose, a mathematical model for a three-echelon supply chain network is created considering the relevant constraints such as capacity, production cost, transport cost, carbon emissions, and time window, which will be solved by the proposed quantum-particle swarm optimization algorithm. The three-echelon supply chain, consisting of suppliers, distribution centers, and retailers, is established based on the number and location of suppliers, the transport method from suppliers to distribution centers, and the quantity of products to be transported from suppliers to distribution centers and from these centers to retailers. Then, a quantum-particle swarm optimization is described as its performance is validated with different benchmark functions. The scenario analysis validates the model and evaluates its performance to balance the economic benefit and environmental effect. © 2018 by the authors.
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英文
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A cognitive reliability model research for complex digital human-computer interface of industrial system
作者：
Jiang, Jianjun* ;Wang, Yiqun;Zhang, Li;Wu, Daqing;Li, Min;...
期刊：
Safety Science ,2018年108:196-202 ISSN：0925-7535
通讯作者：
Jiang, Jianjun
作者机构：
[Jiang, Jianjun; Wang, Yiqun; Zhang, Li; Li, Pengcheng; Xie, Tian; Dai, Licao] Univ South China, Human Factors Inst, Sch Management, Hengyang 421001, Hunan, Peoples R China.;[Jiang, Jianjun; Zhang, Li] Hunan Inst Technol, Sch Safety & Environm Engn, Hengyang 421002, Hunan, Peoples R China.;[Li, Min; Wu, Daqing] Univ South China, Sch Comp Sci & Technol, Hengyang 421001, Hunan, Peoples R China.;[Zhang, Anna; Wang, Shiwei; Shi, Xianyun; Li, Peiyao] Univ South China, Sch Econ & Management, Dept Informat Management & Informat Syst, Grade E Commerce 15, Hengyang 421001, Hunan, Peoples R China.
通讯机构：
[Jiang, Jianjun] U;[Jiang, Jianjun] H;Univ South China, Human Factors Inst, Sch Management, Hengyang 421001, Hunan, Peoples R China.;Hunan Inst Technol, Sch Safety & Environm Engn, Hengyang 421002, Hunan, Peoples R China.
关键词：
Digital human-computer interface;Cognitive reliability model;Bayesian network
摘要：
Nowadays, traditional human–machine interface has been converted into digital human–computer interface in most industrial control rooms, then, cognitive process and reliability are also bound to be different from traditional human–machine interface. Aiming at the situation, the authors in this paper propose a cognitive reliability model with influencing factors based on Bayesian network. Taking a nuclear power plant (Npp) as research background, taking simulative experiment as study way, parameter values in cognitive reliability mathematical model are obtained by analyzing much experimental data. The proposed model is reasonable, accurate, sensitive and convergent by analyzing experiment data. Cognitive error probabilities of some tasks regarding a hot transmission system (HTS) leak accident in a Npp are obtained according to the proposed model and simulative experiments. The model provides a simple and feasible approach to analyze cognitive reliability of operating process in digital human–computer interface. © 2017 Elsevier Ltd
语种：
英文
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Models for Location Inventory Routing Problem of Cold Chain Logistics with NSGA-Ⅱ Algorithm
作者：
郑建国;李康;伍大清
期刊：
东华大学学报(英文版) ,2017年34(4):533-539 ISSN：1672-5220
通讯作者：
Li, K.
作者机构：
[郑建国; 李康] Glorious Sun School of Business and Management, Donghua University, Shanghai, 200051, China;[伍大清] School of Computer Science and Technology, University of South China, Hengyang, 421001, China
通讯机构：
Glorious Sun School of Business and Management, Donghua University, Shanghai, China
关键词：
cold chain logistics;multi-objective;location inventory routing problem （ LIRP ）;non-dominated sorting in genetic algorithm Ⅱ（ NSGA-Ⅱ ）
摘要：
In this paper, a novel location inventory routing (LIR) model is proposed to solve cold chain logistics network problem under uncertain demand environment. The goal of the developed model is to optimize costs of location, inventory and transportation. Due to the complex of LIR problem (LIRP), a multi-objective genetic algorithm (GA), non-dominated sorting in genetic algorithm II (NSGA-II) has been introduced. Its performance is tested over a real case for the proposed problems. Results indicate that NSGA-II provides a competitive performance than GA, which demonstrates that the proposed model and multi-objective GA are considerably efficient to solve the problem. Copyright © 2017 Editorial Board of Journal of Donghua University, Shanghai, China.
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英文
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A novel collaborative optimization algorithm in solving complex optimization problems
作者：
Deng, Wu;Zhao, Huimin* ;Zou, Li;Li, Guangyu;Yang, Xinhua;...
期刊：
Soft Computing ,2017年21(15):4387-4398 ISSN：1432-7643
通讯作者：
Zhao, Huimin
作者机构：
[Zhao, Huimin; Zou, Li; Deng, Wu; Li, Guangyu; Yang, Xinhua] Dalian Jiaotong Univ, Software Inst, Dalian 116028, Peoples R China.;[Zhao, Huimin; Deng, Wu] Guangxi Univ Nationalities, Guangxi Key Lab Hybrid Computat & IC Design Anal, Nanning 530006, Peoples R China.;[Zou, Li; Deng, Wu; Li, Guangyu] Chongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China.;[Zou, Li; Deng, Wu] Southwest Jiaotong Univ, Tract Power State Key Lab, Chengdu 610031, Peoples R China.;[Zhao, Huimin; Deng, Wu] Guangxi Univ Nationalities, Key Lab Guangxi High Sch Complex Syst & Computat, Nanning 530006, Peoples R China.
通讯机构：
[Zhao, Huimin] D;[Zhao, Huimin] G;Dalian Jiaotong Univ, Software Inst, Dalian 116028, Peoples R China.;Guangxi Univ Nationalities, Guangxi Key Lab Hybrid Computat & IC Design Anal, Nanning 530006, Peoples R China.;Guangxi Univ Nationalities, Key Lab Guangxi High Sch Complex Syst & Computat, Nanning 530006, Peoples R China.
关键词：
Genetic algorithm;Ant colony optimization algorithm;Chaotic optimization method;Multi-strategy;Collaborative optimization;Complex optimization problem
摘要：
To overcome the deficiencies of weak local search ability in genetic algorithms (GA) and slow global convergence speed in ant colony optimization (ACO) algorithm in solving complex optimization problems, the chaotic optimization method, multi-population collaborative strategy and adaptive control parameters are introduced into the GA and ACO algorithm to propose a genetic and ant colony adaptive collaborative optimization (MGACACO) algorithm for solving complex optimization problems. The proposed MGACACO algorithm makes use of the exploration capability of GA and stochastic capability of ACO algorithm. In the proposed MGACACO algorithm, the multi-population strategy is used to realize the information exchange and cooperation among the various populations. The chaotic optimization method is used to overcome long search time, avoid falling into the local extremum and improve the search accuracy. The adaptive control parameters is used to make relatively uniform pheromone distribution, effectively solve the contradiction between expanding search and finding optimal solution. The collaborative strategy is used to dynamically balance the global ability and local search ability, and improve the convergence speed. Finally, various scale TSP are selected to verify the effectiveness of the proposed MGACACO algorithm. The experiment results show that the proposed MGACACO algorithm can avoid falling into the local extremum, and takes on better search precision and faster convergence speed.
语种：
英文
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Optimal design methods for a digital human-computer interface based on human reliability in a nuclear power plant: Part 2: The optimization design method for component quantity
作者：
Jiang, Jianjun* ;Zhang, Li;Xie, Tian;Wu, Daqing;Li, Min;...
期刊：
Annals of Nuclear Energy ,2017年106:247-255 ISSN：0306-4549
通讯作者：
Jiang, Jianjun
作者机构：
[Jiang, Jianjun; Zhang, Li] Hunan Inst Technol, Sch Safety & Environm Engn, Hengyang 421002, Hunan, Peoples R China.;[Jiang, Jianjun; Wang, Yiqun; Zhang, Mengjia; Xie, Tian] Univ South China, Sch Econ & Management, Human Factors Inst, Hengyang 421001, Hunan, Peoples R China.;[Li, Min; Wu, Daqing] Univ South China, Sch Comp Sci & Technol, Hengyang 421001, Hunan, Peoples R China.;[Peng, Yuyuan] South China Univ Technol, Guangzhou Coll, Sch Comp Engn, Guangzhou 510830, Guangdong, Peoples R China.;[Peng, Jie] GuangDong Univ Finance & Econ, Informat Sci Coll, Guangzhou 510320, Guangdong, Peoples R China.
通讯机构：
[Jiang, Jianjun] H;[Jiang, Jianjun] U;Hunan Inst Technol, Sch Safety & Environm Engn, Hengyang 421002, Hunan, Peoples R China.;Univ South China, Sch Econ & Management, Human Factors Inst, Hengyang 421001, Hunan, Peoples R China.
关键词：
Affinity error probability mapping function;Human reliability;Quantity of components;Quick convergence search method
摘要：
This is the second in a series of papers describing the optimal design method for a digital human-computer interface of nuclear power plant (Npp) from three different points based on human reliability. The purpose of this series is to explore different optimization methods from varying perspectives. This present paper mainly discusses the optimal design method for quantity of components of the same factor. In monitoring process, quantity of components has brought heavy burden to operators, thus, human errors are easily triggered. To solve the problem, the authors propose an optimization process, a quick convergence search method and an affinity error probability mapping function. Two balanceable parameter values of the affinity error probability function are obtained by experiments. The experimental results show that the affinity error probability mapping function about human-computer interface has very good sensitivity and stability, and that quick convergence search method for fuzzy segments divided by component quantity has better performance than general algorithm. © 2017 Elsevier Ltd
语种：
英文
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A new discrete particle swarm optimization for location inventory routing problem in cold logistics
作者：
Li, Kang;Zheng, Jianguo;Wu, Daqing
期刊：
Revista de la Facultad de Ingeniería Universidad Central de Venezuela ,2016年31(5):89-99 ISSN：0798-4065
作者机构：
[Zheng, Jianguo; Li, Kang] School of Management, Donghua University, Shanghai, 200051, China;[Wu, Daqing] School of Computer Science and Technology, University of South China, Hengyang, 421001, China
摘要：
In order to solve cold logistics network problem under uncertain demand environment, this paper proposes a novel location inventory routing model to optimize costs in cold logistics. The goal of the proposed model is to determine the inventory strategy, numbers of location facilities and vehicle routing decisions. A new discrete particle swarm optimization (DPSO) is introduced to solve this integrated model. Its performance is tested over a real case for the proposed problems. Results indicate that it is considerably efficient and effective to solve the problem.
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英文
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核电厂数字化规程在屏之间布局方法及评价
作者：
蒋建军;张力;王以群;彭玉元;李鹏程;...
期刊：
广东工业大学学报 ,2016年19(3):71-76 ISSN：1007-7162
作者机构：
南华大学经济管理学院人因研究所，湖南衡阳，421001;湖南工学院，湖南衡阳，421002;华南理工大学广州学院计算机工程学院，广东广州，510800;南华大学计算机科学与技术学院，湖南衡阳，421001;[李鹏程; 王以群; 李敏; 张力; 伍大清; 张晓玲; 蒋建军] 南华大学
关键词：
事故规程;人因可靠性;动态标识最短移动路径算法
摘要：
面对数字化系统带来的挑战,以减少同一操纵员在屏之间的移动距离为目标,以核电厂数字化人机界面事故规程为研究对象,以人因可靠性为基础,提出事故规程布局的动态标识最短移动路径算法,并利用神经网络人因可靠性评价方法分析执行过程的可靠性。提出的方法通过实例进行了分析,实验表明提出的方法具有较好的性能,能解决核电厂数字化事故规程在屏之间的自动布局。
语种：
中文
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基于多种群合作协同算法的电力系统调度优化
作者：
刘勇;伍大清;孙莉;杨治平
期刊：
东华大学学报(自然科学版) ,2016年42(1):110-116 ISSN：1671-0444
作者机构：
四川省人工智能重点实验室,四川自贡,643000;[伍大清] 四川省人工智能重点实验室,四川自贡643000;[伍大清] 南华大学计算机科学与技术学院,湖南衡阳421001;[伍大清] 安徽大学教育部计算智能与信号处理重点实验室,安徽合肥230039;[伍大清] 东华大学旭日工商管理学院,上海200051
关键词：
合作协同优化;多种群优化;粒子群优化;环境经济调度
摘要：
为解决电力系统环境经济调度这一复杂多目标约束优化问题,提出一种有效多种群合作协同优化算法,采用多个种群对搜索空间进行搜索,运用新型的速度位移更新方式以及种群周期内拓扑结构重组策略.结果表明,该算法能对解空间进行更加全面、充分的探索,可快速找到一组分布具有尽可能好的逼近性、宽广性和均匀性的最优解集合.将该算法应用到某电力系统的环境经济调度中,其仿真计算结果与其他求解方法结果的对比分析表明,该算法可以有效兼顾全局收敛性和Pareto非劣调度方案的多样性,具有较高的效率以及鲁棒性.
语种：
中文
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Vehicle routing problem with time windows using multi-objective co-evolutionary approach
作者：
Wu, D. Q.* ;Dong, M.;Li, H. Y.;Li, F.
期刊：
International Journal of Simulation Modelling ,2016年15(4):742-753 ISSN：1726-4529
通讯作者：
Wu, D. Q.
作者机构：
[Wu, D. Q.] Shanghai Ocean Univ, Coll Econ & Management, Shanghai 201306, Peoples R China.;[Li, H. Y.; Wu, D. Q.] Univ South China, Comp Sci & Technol Inst, Hengyang 421001, Peoples R China.;[Dong, M.; Wu, D. Q.] Shanghai Jiao Tong Univ, Antai Coll Econ & Management, Shanghai 200240, Peoples R China.;[Wu, D. Q.] Sichuan Univ Sci & Engn, Artificial Intelligence Key Lab Sichuan Prov, Zigong 643000, Peoples R China.;[Wu, D. Q.] Guangxi Univ Nationalities, Key Lab, Guangxi High Sch Complex Syst, Nanning 530004, Peoples R China.
通讯机构：
[Wu, D. Q.] S;[Wu, D. Q.] U;[Wu, D. Q.] G;[Wu, D. Q.] N;Shanghai Ocean Univ, Coll Econ & Management, Shanghai 201306, Peoples R China.
关键词：
Multi-Objective Optimization;Discrete Particle Swarm Optimization;Variable Neighbourhood Search;Vehicle Routing Problem with Time Windows
摘要：
This paper introduces a novel multi-objective algorithm (HMPSO) based on discrete particle swarm optimization (PSO) to solve vehicle routing problems with time windows (VRPTW). The presented HMPSO algorithm was combined with an advanced discrete PSO based on set and variable neighbourhood searches to find Pareto optimal routing solutions. These consisted of a complete routing schedule for serving the customers to minimize the two aims of travelling distance and number of vehicles. To increase the discrete PSO efficiency, a novel decoding scheme based on set was designed, and the variable neighbourhood local search was employed to explore new solutions. The experiment results were showed for a set of the Solomon’s 56 VRPTW. The HMPSO algorithm was compared with some algorithms published in papers with the computational evaluations clearly supporting the high performance of the proposed HMPSO algorithm against other algorithms, and confirming that the HMPSO is an efficient algorithm because of a reasonable computational time and cost in solve VRPTW. © 2016, Vienna University of Technology. All rights reserved.
语种：
英文
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A co-evolutionary particle swarm optimization with dynamic topology for solving multi-objective optimization problems
作者：
Wu, Daqing;Tang, Lixiang;Li, Haiyan;Ouyang, LiJun
期刊：
Advances in modelling and analysis. A, general mathematical and computer tools ,2016年53(1):145-159 ISSN：1258-5769
通讯作者：
Tang, Lixiang(Tanglx0731@126.com)
作者机构：
[Li, Haiyan; Ouyang, LiJun; Wu, Daqing] Computer Science and Technology Institute, University of South China, Hangyang, Hunan, China;[Tang, Lixiang] Department of Business Administration, Hunan University of Finance and Economics, Hunan, 410205, China;[Wu, Daqing] Key Laboratory of Intelligent Computing and Signal Processing, Ministry of Education, Anhui University, Hefei, Anhui Province, 230039, China;[Wu, Daqing] Key Laboratory of Guangxi High Schools for Complex System and Computational Intelligence, Guangxi University for Nationalities, Nanning, 530006, China;[Wu, Daqing] Artificial Intelligence Key Laboratory of Sichuan Province (Sichuan University of Science and Engineering), Zigong, 643000, China
通讯机构：
[Tang, L.] D;Department of Business Administration, China
关键词：
Diversity;Multi-objective optimization;Particle swarm optimizer;Two local best solutions
摘要：
This paper proposes a multi-objective with dynamic topology particle swarm optimization (PSO) algorithm for solving multi-objective problems, named DTPSO. One of the main drawbacks of classical multi-objective particle swarm optimization algorithm is low diversity. To overcome this disadvantage, DTPSO uses two dynamic local best particles to lead the search particles with multiple populations to deal with multiple objectives, and maintains diversity of new found non-dominated solutions via partitioned the searching space into fixed number of cells. The proposed DTPSO is validated through comparisons with other two multi-objective algorithms using established benchmarks and metrics. Simulation results demonstrated that DTPSO shows competitive, if not better, performance as compared to the other algorithms. ©2016, AMSE Press. All rights reserved.
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英文
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Optimal design method for a digital human–computer interface based on human reliability in a nuclear power plant. Part 3: Optimization method for interface task layout
作者：
Jiang, Jianjun* ;Wang, Yiqun;Zhang, Li;Xie, Tian;Li, Min;...
期刊：
Annals of Nuclear Energy ,2016年94:750-758 ISSN：0306-4549
通讯作者：
Jiang, Jianjun
作者机构：
[Jiang, Jianjun; Zhang, Li; Wang, Yiqun; Xie, Tian] Univ South China, Sch Econ & Management, Human Factors Inst, Hengyang 421001, Hunan, Peoples R China.;[Zhang, Li] Hunan Inst Technol, Hengyang 421002, Hunan, Peoples R China.;[Li, Min; Wu, Daqing] Univ South China, Sch Comp Sci & Technol, Hengyang 421001, Hunan, Peoples R China.;[Peng, Yuyuan] S China Univ Technol, Guangzhou Coll, Sch Comp Engn, Guangzhou 510830, Guangdong, Peoples R China.;[Shen, Mengxu; Weng, Mengyun; Xie, Cen; Wang, Shiwei; Li, Peiyao] Univ South China, Sch Econ & Management, Dept Informat Management & Informat Syst, Grade Ecommerce 15, Hengyang 421001, Hunan, Peoples R China.
通讯机构：
[Jiang, Jianjun] U;Univ South China, Sch Econ & Management, Human Factors Inst, Hengyang 421001, Hunan, Peoples R China.
关键词：
Digital human–computer interface;Human reliability;Optimization method;Shortest moving path optimization algorithm
摘要：
This is the last in a series of papers describing the optimal design for a digital human–computer interface of a nuclear power plant (NPP) from three different points based on human reliability. The purpose of this series is to propose different optimization methods from varying perspectives to decrease human factor events that arise from the defects of a human–computer interface. The present paper mainly solves the optimization method as to how to effectively layout interface tasks into different screens. The purpose of this paper is to decrease human errors by reducing the distance that an operator moves among different screens in each operation. In order to resolve the problem, the authors propose an optimization process of interface task layout for digital human–computer interface of a NPP. As to how to automatically layout each interface task into one of screens in each operation, the paper presents a shortest moving path optimization algorithm with dynamic flag based on human reliability. To test the algorithm performance, the evaluation method uses neural network based on human reliability. The less the human error probabilities are, the better the interface task layouts among different screens are. Thus, by analyzing the performance of each interface task layout, the optimization result is obtained. Finally, the optimization layouts of spurious safety injection event interface tasks of the NPP are obtained by an experiment, the proposed methods has a good accuracy and stabilization. © 2016 Elsevier Ltd
语种：
英文
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基于奖惩机制的协同多目标优化算法
作者：
伍大清;邵明;李悛;李康
期刊：
计算机工程 ,2015年41(10): 186-191,198 ISSN：1000-3428
作者机构：
[伍大清] 南华大学计算机科学与技术学院,湖南衡阳421001;[伍大清] 东华大学旭日工商管理学院,上海200051;[伍大清] 教育部计算智能与信号处理重点实验室,合肥230039;上海工程技术大学管理学院,上海,200051;南华大学计算机科学与技术学院,湖南衡阳,421001
关键词：
多目标优化算法;协同;精英学习策略;拓扑结构;奖惩机制
摘要：
为提高已有多目标优化算法在求解高维复杂多目标优化问题上的解集分布性和收敛性,提出一种新的多目标微粒群优化算法。该算法基于多目标协同框架,将多种群奖惩机制进化算法用于求解分解后的若干单目标优化子问题,采用动态环形的拓扑结构,设计一种新型精英学习策略,获得逼近Pareto前沿的最优解集。通过典型的多目标优化函数进行测试验证,结果表明,与现有多目标优化算法相比,该算法不仅具有较好的收敛性能,而且解集分布性更均匀、覆盖范围更广。
语种：
中文
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基于人类社交行为的动态多目标优化
作者：
伍大清;郑建国;朱佳俊;孙莉
期刊：
计算机科学 ,2015年42(8):249-252,278 ISSN：1002-137X
作者机构：
[伍大清] 南华大学计算机科学与技术学院 衡阳421001;[伍大清] 成都大学模式识别与智能信息处理四川省重点实验室 成都610106;[伍大清] 东华大学旭日工商管理学院 上海200051;江南大学商学院 无锡214000;[朱佳俊] 江南大学
关键词：
多目标优化算法;精英粒子;平庸粒子;局部跳出策略
摘要：
为了提高多目标微粒群优化算法处理多目标优化问题的性能,降低计算复杂度,改善算法的收敛性,提出了一种基于人类社交行为的多目标动态微粒群优化算法。考虑到粒子寻优过程受到环境中精英粒子与平庸粒子的影响,分别对自身产生推力与阻力作用,并引入局部跳出策略,使算法具有很强的全局搜索能力和较好的鲁棒性能。通过典型的多目标优化函数对算法进行了测试验证,结果表明提出的多目标算法具有较快的收敛速度和较强的跳出局部最优能力,性能优越,可供许多领域优化问题求解借鉴。
语种：
中文
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生鲜农产品冷链物流配送干扰管理研究的思考
作者：
李康;郑建国;伍大清
期刊：
江苏农业科学 ,2015年(11):588-591 ISSN：1002-1302
作者机构：
东华大学旭日工商管理学院,上海,200051;[伍大清] 东华大学旭日工商管理学院，上海 200051;南华大学计算机科学与技术学院，湖南衡阳 421001;人工智能四川省重点实验室，四川自贡 643000;[李康; 郑建国] 东华大学旭日工商管理学院
关键词：
生鲜农产品;冷链;物流配送;干扰管理
摘要：
通过对比国内外干扰管理研究的文献资料,提出了生鲜农产品冷链物流配送干扰管理研究的必要性;在此基础上归纳了其产生干扰管理问题的主要环节,最后就相关问题的进一步研究提出了几点思考。
语种：
中文
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An efficient co-evolutionary particle swarm optimizer for solving multi-objective optimization problems
作者：
Wu, Daqing* ;Liu, Li;Gong, XiangJian;Deng, Li
期刊：
Proceedings of the 2015 27th Chinese Control and Decision Conference, CCDC 2015 ,2015年:1975-1979 ISSN：1948-9439
通讯作者：
Wu, Daqing
作者机构：
[Wu, Daqing] Anhui Univ, Minist Educ, Key Lab Intelligent Comp & Signal Proc, Hefei 230039, Anhui, Peoples R China.;[Liu, Li; Gong, XiangJian; Wu, Daqing] Univ South China, Comp Sci & Technol Inst, Hengyang 421001, Hunan, Peoples R China.;[Deng, Li; Wu, Daqing] DongHua Univ, Glorious Sun Sch Business & Management, Shanghai 200051, Peoples R China.
通讯机构：
[Wu, Daqing] A;Anhui Univ, Minist Educ, Key Lab Intelligent Comp & Signal Proc, Hefei 230039, Anhui, Peoples R China.
会议名称：
The 27th Chinese Control and Decision Conference (2015 CCDC)
会议时间：
May 2015
会议地点：
Qingdao, China
会议主办单位：
[Wu, Daqing] Anhui Univ, Minist Educ, Key Lab Intelligent Comp & Signal Proc, Hefei 230039, Anhui, Peoples R China.^[Wu, Daqing;Liu, Li;Gong, XiangJian] Univ South China, Comp Sci & Technol Inst, Hengyang 421001, Hunan, Peoples R China.^[Wu, Daqing;Deng, Li] DongHua Univ, Glorious Sun Sch Business & Management, Shanghai 200051, Peoples R China.
会议论文集名称：
The 27th Chinese Control and Decision Conference (2015 CCDC)
关键词：
Multi-objective Optimization;Particle Swarm Optimizer;Neighborhood Best Particle;Dynamic Swarms;Economic Environmental Dispatch
摘要：
An efficient co-evolutionary multi-objective particle swarm optimizer named ECMPSO was proposed. ECMPSO uses dynamic multiple swarms to deal with multiple objectives, taking one objective is optimized by each swarm into account, and maintains diversity of new found non-dominated solutions via adopts a three-level particle swarm optimization(PSO) updating rule wherein the particles learn their experiences based on personal, neighborhood, and external archive. To prove the validity of the ECMPSO algorithm for solving multi-objective problems, some benchmark problems and one real-life problem are selected to validate the performance of the ECMPSO algorithm. The experiment results show that the ECMPSO algorithm is better in terms of search precision and convergence performance than other three algorithms from the literature.
语种：
英文
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生鲜农产品冷链管理及关键技术研究进展
作者：
李康;郑建国;伍大清
期刊：
食品与机械 ,2015年31(6):233-237 ISSN：1003-5788
作者机构：
[李康; 郑建国] 东华大学旭日工商管理学院;[伍大清] 南华大学计算机科学与技术学院
关键词：
生鲜;农产品;冷链管理;供应链
摘要：
冷链已经成为世界各国提高生鲜农产品流通条件、食品质量安全、农产品附加值及促进农产品走向国际市场的重要保障。与世界发达国家相比,中国的生鲜农产品冷链在技术、整体设备拥有量和系统管理水平等方面均存在一定的差距。在对国内外冷链管理研究进行梳理的基础上,对冷链管理中的几类主要问题:库存、物流系统规划、质量安全、协调机制及关键技术等进行综述和比较分析,最后从生鲜农产品冷链碳排放、消费者行为倾向、闭环供应链等方面探讨中国未来生鲜农产品冷链的发展趋势。
语种：
中文
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基于毕业生求职视角的一种新型实践教学模式
作者：
伍大清;刘立;李悛;罗江琴
期刊：
计算机教育 ,2015年(3):62-64 ISSN：1672-5913
作者机构：
南华大学计算机科学与技术学院,湖南衡阳,421001;[李悛; 罗江琴; 伍大清; 刘立] 南华大学
关键词：
计算机;本科;求职;实习模式
摘要：
阐述计算机大学毕业生求职的现实基础上,分析传统的实践教学应该需要加以改进,提出学校和企业合作的“双师”指导模式.
语种：
中文
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基于人因可靠性的核电厂数字化人机界面功能单元数量优化方法
作者：
蒋建军;张力;王以群;彭玉元;李敏;...
期刊：
原子能科学技术 ,2015年49(10):1876-1881 ISSN：1000-6931
作者机构：
[张力; 青涛; 蒋建军; 李鹏程; 王以群] Human Factors Institute, School of Economic &, Management, University of South China, Hengyang, China;[张晓玲; 伍大清] School of Computer Science and Technique, University of South China, Hengyang, China;[李敏] Networks Center, University of South China, Hengyang, China;[彭玉元] School of Computer Engineering, Guangzhou College of South China University of Technology, Guangzhou, China;[张力] Hunan Institute of Technology, Hengyang, China
关键词：
核电厂数字化人机界面;构件数量;取中查找提取方法;失误亲和率函数
摘要：
核电厂数字化人机界面功能块中的构件数量给操纵员带来了极大负荷并影响人误事件的发生。本文对功能块中的参数数量建立了一完整的优化流程图,对流程图中的几个关键部分进行详细研究:对因子数量采用动态模糊分段法产生模糊数量段;在模糊数量段因子的搜索中,建立了模糊数量段的取中查找提取方法,大幅提高了搜索性能;对人机界面参数量设计了失误亲和率函数。试验结果表明:模糊数量段的取中查找提取方法明显优于顺序查找提取方法,失误亲和率函数具有较好的稳定性、收敛性及灵敏度。
语种：
中文
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基于慕课的翻转课堂实战化教学模式构建
作者：
伍大清;阳小华;刘志明;吴取劲
期刊：
计算机教育 ,2015年(5):78-80 ISSN：1672-5913
作者机构：
南华大学计算机科学与技术学院,湖南衡阳,421001;[刘志明; 吴取劲; 阳小华; 伍大清] 南华大学
关键词：
慕课;翻转课堂;启发式教学模式;个性化
摘要：
随着慕课的推广,翻转课堂已成为教育界关注的教学模式。文章针对慕课的优势与对学习者和教师的要求,提出基于慕课的翻转课堂实战化教学模式,并结合具体专业课程开展实践研究,初步验证该模式的有效性。
语种：
中文
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