求旅行商问题近似解的碰撞算法

提出通过寻找精确解的边获得旅行商问题(TSP)近似解的思想,并以该思想为指导,设计一种新的碰撞算法。对国际通用的TSPLIB中不同城市规模的数据进行测试表明,该算法可以得到与目前已知最优解或相同或相近的结果。该算法不仅可以计算小规模的TSP,而且同样适用较大规模的TSP。     

A branch-and-cut algorithm for the minimum labeling Hamiltonian cycle problem and two variants

This paper proposes a mathematical model, valid inequalities and polyhedral results for the minimum labeling Hamiltonian cycle problem. This problem is defined on an unweighted graph in which each edge has a label. The aim is to determine a Hamiltonian cycle with the least number of labels. We also define two variants of this problem by assigning weights to the edges and by considering the tour length either as an objective or as a constraint. A branch-and-cut algorithm for the three problems is developed, and computational results are reported on randomly generated instances and on modified instances from TSPLIB.     

The balanced traveling salesmanproblem

In this paper we introduce the balanced traveling salesman problem (BTSP), which can be used to model optimization problems where equitable distribution of resources are important. BTSP is obviously NP-hard. Efficient heuristic algorithms are presented to solve the problem along with extensive computational results using benchmark problems from TSPLIB and random instances. Our algorithms produced provably optimal solutions for several test instances. Application of the model in solving the nozzle guide vane assembly problem related to the maintenance of aircraft engines is also discussed.     

台达VE系列变频器在桥式起重机中的应用

本文介绍了桥式起重机的工作原理和应用环境,详细阐述了台达VFD—VE系列变频器应用于行车电动机的变频驱动原理与功能模式。为VFD—VE变频器在行车行业中的应用提供了参考。     

面向TSP求解的混合蚁群算法

针对蚁群算法的早熟和停滞等现象,将免疫算法机制引入蚁群算法,提出用于TSP求解的混合算法。该算法具有蚁群算法的自适应反馈机理、收敛速度快和免疫算法操作算子简单和维持种群多样性、防止种群退化等特性。从算法解的质量与效率方面与基本蚁群算法和免疫算法进行比较,结果表明融合免疫机制的蚁群算法性能显著提高,也为解决其他组合优化问题提供一个新的思路。     

Intelligent adaptive observer-based optimal control of overhead transmission line de-icing robot manipulator

In cold season, wet snow ice accretion on overhead transmission lines increases wind load effects which in turn increases line tension. This increased line tension causes undesirable effects in power systems. This paper discusses the design of an observer-based boundary sliding mode control (BSMC) for 3 DOF overhead transmission line de-icing robot manipulator (OTDIRM). A robust radial basis functional neural network (RBFNN) observer-based neural network (NN) controller is developed for the motion control of OTDIRM, which is a combination of BSMC, NN approximation and adaptation law. The RBFNN-based adaptive observer is designed to estimate the positions and velocities. The weights of both NN observer and NN approximator are tuned off-line using particle swarm optimization. Using Lyapunov analysis the closed loop tracking error was verified for a 3 DOF OTDIRM. Finally, the robustness of the proposed neural network-based adaptive observer boundary sliding mode control (NNAOBSMC) was verified against the input disturbances and uncertainties.     

Cooperative group optimization with ants (CGO-AS): Leverage optimization with mixed individual and social learning

We present CGO-AS, a generalized ant system (AS) implemented in the framework of cooperative group optimization (CGO), to show the leveraged optimization with a mixed individual and social learning. Ant colony is a simple yet efficient natural system for understanding the effects of primary intelligence on optimization. However, existing AS algorithms are mostly focusing on their capability of using social heuristic cues while ignoring their individual learning. CGO can integrate the advantages of a cooperative group and a low-level algorithm portfolio design, and the agents of CGO can explore both individual and social search. In CGO-AS, each ant (agent) is added with an individual memory, and is implemented with a novel search strategy to use individual and social cues in a controlled proportion. The presented CGO-AS is therefore especially useful in exposing the power of the mixed individual and social learning for improving optimization. The optimization performance is tested with instances of the traveling salesman problem (TSP). The results prove that a cooperative ant group using both individual and social learning obtains a better performance than the systems solely using either individual or social learning. The best performance is achieved under the condition when agents use individual memory as their primary information source, and simultaneously use social memory as their searching guidance. In comparison with existing AS systems, CGO-AS retains a faster learning speed toward those higher-quality solutions, especially in the later learning cycles. The leverage in optimization by CGO-AS is highly possible due to its inherent feature of adaptively maintaining the population diversity in the individual memory of agents, and of accelerating the learning process with accumulated knowledge in the social memory.     

人工神经网络求解TSP问题新方法

本文在分析Hopfield/Tank方法的基础上提出一种新的人工神经网络方法,采用优化约束条件的能量函数,具有收敛速度快、不易陷入无效解、易获得亚优解等优点。     

可共享的,跨平台的网络数字图像处理技术

本文对Internet上进行数字图像处理的技术做了深入的研究,并在技术上采用了现今比较流行的webB/S架构和JAVA语言,从而构造出了一个比较完整的在线网络图像处理模式。最后采用了SUN公司推出的struts轻量级构架编写一个数字图像处理的软件包,名为“myapp”,并附带在tomcat服务器上的“webapp”文件夹下,用户只要启动该服务器,即可登录“http://localhost:8080/myapp/Param/picture.jsp”进行数字图像处理了。注意,这里的tomcat服务器只做本地机器测试用途,也可将工程文件“myapp”导入大型服务器(如weblogic等),进行全网络共享。     

用PLC实现中型立体仓库控制

提出了一种用PLC实现中型立体仓库自动控制方法。立体仓库系统的运行表明堆垛机三维定位控制精确,运行可靠。