Description: 八皇后问题是一个古老而著名的问题，是回溯算法的典型例题。该问题是十九世纪著名的数学家高斯1850年提出：在8X8格的国际象棋上摆放八个皇后，使其不能互相攻击，即任意两个皇后都不能处于同一行、同一列或同一斜线上，问有多少种摆法。-8 Queen s problem is an ancient and well-known problems, backtracking algorithm is a typical example. The problem is that the nineteenth century, the famous mathematician Gauss in 1850: Under the 8x8 grid on the display of the chess Queen eight, making it unable to attack each other, that is, any two can not be Queen s in the same line, the same row or the same slash on, asking how many kinds of pendulum method. Platform: |
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Author:何再兴 |
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Description: 简单遗传算法，程序进化一个沿二维网格边界行走的机器人。-Simple genetic algorithm, the program evolved a two-dimensional grid along the border walking robots. Platform: |
Size: 32768 |
Author:lml |
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Description: Grid technologies have progressed towards a service-oriented paradigm that enables a new way
of service provisioning based on utility computing models, which are capable of supporting diverse
computing services. It facilitates scientific applications to take advantage of computing resources
distributed world wide to enhance the capability and performance. Many scientific applications in areas
such as bioinformatics and astronomy require workflow processing in which tasks are executed based on
their control or data dependencies. Scheduling such interdependent tasks on utility Grid environments need
to consider users’ QoS requirements. In this paper, we present a genetic algorithm approach to address
scheduling optimization problems in workflow applications, based on two QoS constraints, deadline and
budget.
Keywords: Grid workflow Platform: |
Size: 216064 |
Author:miren |
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Description: Abstract. In this paper, we present a scheduler for distributing workflows in Utility Management System (UMS).
The system executes a large number of workflows, which have very high resource requirements. The workflows have
different computational requirements and thus the optimization of resource utilization must be performed in a way that
is different from the standard approach of scheduling workflows. We developed a strategy for allocating workflows,
which is based on a genetic algorithm. The proposed architecture executes a scheduling algorithm by using a feedback
from the execution monitor. We also report on an experimental study, which shows that a significant improvement of
overall execution time can be achieved by using the genetic algorithm. The algorithm is used for designing effective
Grid schedulers that optimize makespan. The study further shows that the overall system (UMS) performance is
significantly improved this finding indicates that there can be reduction in hardware investment.-Abstract. In this paper, we present a scheduler for distributing workflows in Utility Management System (UMS).
The system executes a large number of workflows, which have very high resource requirements. The workflows have
different computational requirements and thus the optimization of resource utilization must be performed in a way that
is different from the standard approach of scheduling workflows. We developed a strategy for allocating workflows,
which is based on a genetic algorithm. The proposed architecture executes a scheduling algorithm by using a feedback
from the execution monitor. We also report on an experimental study, which shows that a significant improvement of
overall execution time can be achieved by using the genetic algorithm. The algorithm is used for designing effective
Grid schedulers that optimize makespan. The study further shows that the overall system (UMS) performance is
significantly improved this finding indicates that there can be reduction in hardware investment. Platform: |
Size: 172032 |
Author:nemanja |
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Description: 本文主要研究 LS-SVM 算法的基本原理及基于其实现时间序列预测
的方法。针对超参数选择困难的问题，采用多级网格搜索和遗传算法的方法对
超参数的取值进行优化-This paper studies the basic principles of the LS-SVM algorithm and time series prediction based on its implementation. Difficult to select for hyper parameter, multi-level grid search and genetic algorithm to optimize the values of hyper parameters Platform: |
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Author:毛玉凤 |
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Description: 用于微电网在电力系统中的改进遗传算法优化，仿真运行-Improved Genetic Algorithm for micro-grid power system optimization, simulation run Platform: |
Size: 1024 |
Author:jjsky |
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Description: 在一个小型分布式发电系统的基础上, 建立分布式供能系统的调度策略和经济调度模型, 通过考虑各种电源的约束条件, 用改进的遗传算法进行求解, 使得分布式微网系统能够实现热电联供, 满足用户的需求. 算例系
统验证了模型与算法的可行性。-On the basis of a small distributed generation systems established on the scheduling policy and economic dispatch model of distributed energy supply system by considering various power constraints, improved genetic algorithm to solve such a distributed micro-grid system can achieve thermoelectric cogeneration, to meet the needs of users. Example system Operator
System to verify the feasibility of the model and algorithm. Platform: |
Size: 267264 |
Author:伍健全 |
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Description: 微电网经济优化运行.PDF 含储能的主动配电网优化运行研究 含多微网的主动配电系统综合优化运行行为分析与建模 基于遗传算法的热电联产型微网经济运行优化-Micro grid economic optimization operation. PDF with energy storage in active distribution network optimal operation with multi microgrid active distribution system integrated optimization operation behavior analysis and modeling based network economic operation optimization of a genetic algorithm for CHP microgrid
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Size: 2370560 |
Author:苗苗 |
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Description: 基于遗传算法的IEEE30节点无功优化程序，针对电网的电压损耗作为目标函数进行了优化，优化的目标是使得网损达到最小值。-IEEE30 node reactive power optimization based on genetic algorithm, in view of the grid voltage loss as objective function is optimized, the goal of optimization is to achieve minimum network loss. Platform: |
Size: 25600 |
Author: |
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Description: This paper presents an intelligent-based algorithm for
sizing grid-connected photovoltaic (GCPV) system using Genetic
Algorithm (GA). GA had been used to determine the optimal PV
module and inverter pre-developed PV module and inverter
databases such that the expected technical performance of the
design could be optimized-This paper presents an intelligent-based algorithm for
sizing grid-connected photovoltaic (GCPV) system using Genetic
Algorithm (GA). GA had been used to determine the optimal PV
module and inverter pre-developed PV module and inverter
databases such that the expected technical performance of the
design could be optimized Platform: |
Size: 325632 |
Author:hojjat |
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Description: 建立LibSVM预测模型，基于网格算法、粒子群算法、遗传算法优化了模型参数，并由最终模型预测了给定切削参数下零件的粗糙度等级。-Establish LibSVM prediction model, grid-based algorithm, particle swarm optimization, genetic algorithm to optimize the parameters of the model, the final model prediction given by the cutting parameters of parts roughness class. Platform: |
Size: 650240 |
Author:墨非 |
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Description: 文章以含有蓄电池、光伏、风机以及负荷的微电网为研究对象，在考虑蓄电池充放电约束、微电网与电网功率交换约束等条件下，建立了以负荷平均供电单价最小为目标的日前优化调度模型。并利用改进交叉算子的遗传算法进行求解。以某典型微电网为例进行建模与求解，得到了微电网日前优化调度方案，实现了微电网的经济稳定运行(Taking the micro-grid with storage battery, photovoltaic, fan and load as the research object, considering the battery charging and discharging constraints, power exchange constraints between micro-grid and power grid, a daily optimal dispatching model with the objective of minimizing the average unit price of power supply is established. The improved crossover operator is used to solve the genetic algorithm. Taking a typical micro-grid as an example, the day-ahead optimal dispatching scheme of micro-grid is obtained, and the economic and stable operation of micro-grid is realized.) Platform: |
Size: 172032 |
Author:阿飞之父 |
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Description: 路径规划，基于一种遗传算法的路径规划方法，利用栅格法，成功实现了避障路径规划。(Path planning, a method of path planning based on genetic algorithm and grid method, has successfully realized obstacle avoidance.) Platform: |
Size: 6144 |
Author:不二345 |
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Description: 采用栅格对机器人的工作空间进行划分，再利用优化算法对机器人路径优化，是采用智能算法求最优路径的一个经典问题。目前，采用蚁群算法在栅格地图上进行路径优化取得比较好的效果，而利用遗传算法在栅格地图上进行路径优化在算法显得更加难以实现。
利用遗传算法处理栅格地图的机器人路径规划的难点主要包括：1保证路径不间断，2保证路径不穿过障碍。
用遗传算法解决优化问题时的步骤是固定的，就是种群初始化，选择，交叉，变异，适应度计算这样，那么下面我就说一下遗传算法求栅格地图中机器人路径规划在每个步骤的问题、难点以及解决办法。(It is a classical problem to divide the workspace of the robot by grids and optimize the path of the robot by using optimization algorithm. At present, the ant colony algorithm is used to optimize the path on the grid map, and the genetic algorithm is used to optimize the path on the grid map, which is more difficult to achieve.
The difficulties of using genetic algorithm to deal with the path planning of robot on raster map mainly include: 1. guaranteeing that the path is uninterrupted, 2. guaranteeing that the path does not cross obstacles.
The steps of genetic algorithm in solving optimization problems are fixed, that is, population initialization, selection, crossover, mutation, fitness calculation. Then I will talk about the problems, difficulties and solutions of genetic algorithm in each step of robot path planning in raster map.) Platform: |
Size: 5120 |
Author:adkuhd8wy |
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Search - Grid genetic algorithm