搜索资源列表
multiobjective_GA
- 多目标进化计算算法在JGAP包上的实现。程序演示了多目标进化中fitness function和search operator的实现。-Multi-objective evolutionary computation algorithm in the realization of JGAP package. Procedures to demonstrate the evolution of multi-objective fitness function and the realization
TSP_GA
- 使用进化计算算法解决TSP（Travelling Sales man Problem）问题的算法实现。程序显示了进化计算在解决NP-Hard的传统难题上的优势。-The use of evolutionary computation algorithm to solve TSP (Travelling Sales man Problem) algorithm problem.
gViz1.1
- Recently, both to return to my old love for evolution and to broaden my research horizon, I have started working on models simulating the dynamics of evolutionary processes. It is becoming clearer and clearer in biology that to understand form,
bifarea
- Recently, both to return to my old love for evolution and to broaden my research horizon, I have started working on models simulating the dynamics of evolutionary processes. It is becoming clearer and clearer in biology that to understand form,
Main1
- this genetic algorithm in evolutionary algorithm
GA-VC
- 遗传算法（Genetic Algorithm）是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法。压缩包中包含了由C++语言编写的算法。-Genetic Algorithm (Genetic Algorithm) is a simulation of the biological theory of evolution Darwin' s natural selection and genetic mechanism of th
mingtiyanhuajisuan
- 命题演化计算，关于离散数学的数值式自动求值。-Proposition evolutionary computation, discrete mathematics on the automatic numerical evaluation.
opt4j-2.0
- Java平台的启发式优化算法，包含了多目标进化算法（SPEA2和NSGA2），多目标差异进化，PSO和单目标模拟退火算法。并且包含了ZDT,DTLZ和WFG等测试函数-Opt4J is a framework for applying meta-heuristic optimization algorithms to arbitrary optimization problems. The Opt4J framework currently includes a multi-obje
pavel_1.0.1beta_setup
- Pavel是一个交互式显示和评估高维数据的工具，主要用对多目标进化算法结果的分析。-Pavel (Paretoset Analysis Visualization and Evaluation) is a tool for interactively displaying and evaluating large sets of highdimensional data. Its main intended use is the analysis of result sets from mult
pso_vcpp
- 粒子群算法 粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation)，有 Eberhart博士和kennedy博士发明。源于对鸟群捕食的行为研究PSO同遗传算法类 似，是一种基于叠代的优化工具。系统初始化为一组随机解，通过叠代搜寻最优 值。但是并没有遗传算法用的交叉(crossover)以及变异(mutation)。而是粒子在 解空间追随最优的粒子进行搜索。-pso 粒子群优化算法(PSO)是一种进化计算技术(evolutionary
Othello
- 使用java编写的GUI的黑白棋游戏，搜索算法采用经典的博弈树，并在此基础上做了大量优化，我的评估函数采用了Simon M. Lucas 和 Thomas P. Runarsson 在其合作发表的 Temporal Difference Learning Versus Co-Evolution for Acquiring Othello Position Evaluation 中通过对比即时差分学习（TDL，Temporal Difference Learning）和协同进化（CEL，Co-
EvolutionaryAlgorithm
- 本例用演化算法处理了函数f=x^2在[1,31]上的极值问题。关键词：二进制编码，轮盘赌模型-Evolutionary algorithm used in this case to deal with the function f = x ^ 2 in [1,31] on the extremal problem. Keywords: binary code, roulette model
EvolutionaryAlgorithmsforSolvingMulti-ObjectivePro
- 《Evolutionary Algorithms for Solving Multi-Objective Problems》这是一本有关多目标进化的非常值得一看的书，里面有测试标准，测试函数等内容-The solving of multi-objective problems (MOPs) has been a continuing effort by humans in many diverse areas, including computer science, engineering, e
MOPandGA
- 使用强变异演化算法处理高维决策向量情况下的多目标优化问题-Strong variation of the use of evolutionary algorithms to deal with high-dimensional vector in decision-making in case of multi-objective optimization problem
080502
- 基于MATLAB的蚁群算法仿真研究 ：介绍了基于MATLAB的蚁群算法仿真研究。对佛罗里达州六城市旅行商问题进行了MATLAB仿真，计算结果显示，作为新型 进化算法，蚁群算法能够解决复杂组合优化问题。-Ant colony algorithm based on MATLAB Simulation: This paper introduces the ant colony algorithm based on the MATLAB simulation. Six Cities of Flo
evo-knapsack
- pdf for evolutionary computing of knapsack
Printed_Circuits
- This edition addresses these new elements of the printed circuit processes, both revolutionary and evolutionary, while still maintaining its foundation on the basics of the technology.No matter how sophisticated the leading edge of the technology
java_evolutionary_algorithms
- 用Java实现的进化算法包。包括遗传算法、粒子群算法、memetic算法和进化策略算法。-evolutionary-algorithm Evolutionary Algorithm package implemented using Java. The package serves as a foundation class library, supporting the implementation many variants of Evolutionary Algorith
featureselectionEP
- feature selection using evolutionary algorithm
Netcode2006
- On Minimizing Network Coding Resources: An Evolutionary Approach