基于量子遗传算法的光电干扰资源优化分配研究

结合光电信息系统作战运筹中目标分配原则,建立了干扰资源优化分配模型。给出了基于量子遗传算法的模型求解方法及步骤,并进行了实例仿真,得出了最佳干扰资源分配方案。仿真结果表明,该方法优于遗传算法,对于求解干扰资源优化分配模型是有效、可行的。     

基于遗传算法的地铁列车自动驾驶控制算法研究

轨道交通列车运行曲线的控制是轨道交通列车自动化的核心技术。通过提出改进的遗传算法来设计列车ATO（列车自动驾驶）控制算法，使用某城市地铁列车参数建模，编制实用的遗传算法生成列车时分控制曲线的程序，并进行计算机仿真，仿真的结果达到了：输出时间与给定的定时值完全一致；能耗比节时模式降低56%；停车点精度｜x｜=14cm，小于规定值（25cm）；最大速度小于规定值；具有较高的全局适应度。表明算法效果良好、性能优越。     

Generating complete all-day activity plans with genetic algorithms

Activity-based demand generation contructs complete all-day activity plans for each member of a population, and derives transportation demand from the fact that consecutive activities at different locations need to be connected by travel. Besides many other advantages, activity-based demand generation also fits well into the paradigm of multi-agent simulation, where each traveler is kept as an individual throughout the whole modeling process. In this paper, we present a new approach to the problem, which uses genetic algorithms (GA). Our GA keeps, for each member of the population, several instances of possible all-day activity plans in memory. Those plans are modified by mutation and crossover, while bad instances are eventually discarded. Any GA needs a fitness function to evaluate the performance of each instance. For all-day activity plans, it makes sense to use a utility function to obtain such a fitness. In consequence, a significant part of the paper is spent discussing such a utility function. In addition, the paper shows the performance of the algorithm to a few selected problems, including very busy and rather non-busy days.     

基于模拟退火算法的运梁车转向机构优化设计

建立了运梁车液压连杆转向机构优化数学模型。考虑车辆在转向时的各种影响因素,以转向机构转向的平稳性、传动性能、利用效率为多优化目标。利用快速的模拟退火算法进行优化求解,以避免陷入局部极值,加快收敛速度。仿真结果显示它使转向机构的综合性能得到了较大的改善。     

基于遗传算法的操舵仪控制参数在线优化

采用遗传算法对航向保持自动操作仪控制参数进行在线优化,计算机仿真表明,遗传算法可以方便地得到全局最优解,故控制器可以快速稳定地跟踪预定航向,且系统具有较好的鲁棒性。     

广义Gauss模型及其模拟退火算法

研究了求解优化问题全局解的随机神经网络方法，将Gauss模型拓展为广义Gauss模型，使之能求解一般优化问题的全局解。进而引入全局性较好的模拟退火算法的思想，提出了广义Gauss模型的模拟退火算法。通过算例比较了几种计算智能算法的全局性。广义Gauss模型的模拟退火运行全局性最好，但它付出了时间的代价；广义Gauss模型兼顾了计算效率和全局性；广义Hopfield网络的全局性最不理想。     

Bridging the gap between multi-objective optimization and spatial planning: a new post-processing methodology capturing the optimum allocation of land uses against established transportation infrastructure

The optimal allocation of multiple land uses constitutes a complex multi-objective optimization problem with unknown feasible objective space and optimal planning alternatives. Despite the effectiveness of evolutionary algorithms to capture the underlying Pareto set of optimum maps, land use planners are bound to pursue the best possible spatial allocation of each use within an enormous population of non-dominated solutions. This article presents a novel post-processing methodology enhancing the comparative evaluation of alternative planning approaches without making any assumptions about the (relative) importance of each objective function. The proposed consolidated post-processing module is applied in a land use planning paradigm, revealing: (a) the existence of substantial planning guidelines whose validity is not affected by the relative significance of each criterion and (b) the variable planning component emerging from the (varying) relative importance of objective functions. Such planning feedback could not be extracted by the exhaustive review of non-dominated maps.     

区段站阶段计划的优化模型和算法

以区段站阶段内准点满轴发车为目标,建立混合０－１规划模型,并根据大系统理论将系统分解为４个有序的子系统,同时给出分解算法,为阶段计划的计算机自动编制提供了一个优化决策基础。     

单线铁路平行运行图通过能力的遗传算法

在分析单线铁路成对非追踪平行运行图区间通过能力整数规划模型的基础上提出了该模型的遗传算法,经经验,用该算法解决单线铁路平行运行图的区间通过能力计算问题行之有效的。     

SOFT COMPUTING APPROACH FOR NOISY IMAGE RESTORATION

IntroductionSoftcomputing is a consortium of different com-puting tools to deal with real world problems ef-ficiently.The aim of softcomputing is to exploitthe tolerance for imprecision and uncertainty toachieve tractability,robustness and low cost[1] .Neurocomputing is one of the major componentsof soft computing,the other two important con-stituents are fuzzy logic and probabilistic reason-ing,which subsumes belief networks,geneticalgorithms and chaotic systems.Often,to solvea fairly complex…