Search - evolutionary algorithms

Search - evolutionary algorithms - List

[Other] cvrp DL : 0: 蚁群算法是近年来出现的一种新德仿生类进化算法[8]，它的基本原理源于昆虫学家们的观察和发现 -ant algorithms, which is the emergence of a new category of bionic Germany evolutionary algorithm [8] it stems from the basic tenets of the entomologist observed and found
Date : 2025-12-28 Size : 2kb User : 黄如尚
[Other] WS_net DL : 0: 复杂网络上演化博弈的小世界网络的算法等等希望有用-Evolutionary Game on Complex Networks of small world network of algorithms, and so wish to be useful
Date : 2025-12-28 Size : 2kb User : 寇亮
[Other] my_ga DL : 0: Rudolph G. Convergence analysis of canonical genetic algorithms. IEEE Trans. On Neural Networks, 1994,5:96~101 [36] Rudolph G. Asymptotic convergence rates of simple evolutionary algorithms with Cauchy mutations. IEEE Transactions on Evolutionary Computation, 1998,1(4):249~258 [37] Srinivas M, Patnaik L M. Adaptive Probabilities of Crossover and Mutations in Gas. I-Rudolph G. Convergence analysis of canonical genetic algorithms. IEEE Trans. On Neural Networks, 1994,5:96~101 [36] Rudolph G. Asymptotic convergence rates of simple evolutionary algorithms with Cauchy mutations. IEEE Transactions on Evolutionary Computation, 1998,1(4):249~258 [37] Srinivas M, Patnaik L M. Adaptive Probabilities of Crossover and Mutations in Gas. IEEE
Date : 2025-12-28 Size : 5kb User : lfq
[Other] LivingMachinesUseofGeneticalAlgorithms DL : 0: Genetic Algorithms (GAs) are adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. The basic concept of GAs is designed to simulate processes in natural system necessary for evolution, specifically those that follow the principles first laid down by Charles Darwin of survival of the fittest. As such they represent an intelligent exploitation of a random search within a defined search space to solve a problem. Not only does GAs provide an alternative method to solving problem, it consistently outperforms other traditional methods in most of the problems link. Many of the real world problems involved finding optimal parameters, which might prove difficult for traditional methods but ideal for GAs.
Date : 2025-12-28 Size : 149kb User : raj
[Other] Others DL : 0: Cultural Algorithms is a fast and robust evolutionary algorithm
Date : 2025-12-28 Size : 2kb User : mehdi
[Other] SpeedyGA DL : 0: genetic algorithm In the field of artificial intelligence, a genetic algorithm (GA) is a search heuristic that mimics the process of natural selection. This heuristic (also sometimes called a metaheuristic) is routinely used to generate useful solutions to optimization and search problems.[1] Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.
Date : 2025-12-28 Size : 3kb User : siddhuu
[Other] classical-GA-method DL : 0: 遗传算法是计算机科学人工智能领域中用于解决最优化的一种搜索启发式算法，是进化算法的一种。这种启发式通常用来生成有用的解决方案来优化和搜索问题。进化算法最初是借鉴了进化生物学中的一些现象而发展起来的，这些现象包括遗传、突变、自然选择以及杂交等。-In the field of artificial intelligence, a genetic algorithm (GA) is a search heuristic that mimics the process of natural selection. This heuristic (also sometimes called a metaheuristic) is routinely used to generate useful solutions to optimization and search problems.[1] Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.
Date : 2025-12-28 Size : 3kb User : liu
[Other] multi-objective-Optimization-Using-Evolutionary-A DL : 0: multi-objective Optimization Using Evolutionary Algorithms 论文对应的matlab代码
Date : 2025-12-28 Size : 171kb User : Zhang
[Other] nsga2.tar DL : 0: 这段代码描述多目标遗传算法NSGAII算法的实现，抓要包含三部分：Non-dominated sort， Crowding distance assignment， the selection process来找到pareto-front-The basic operations being performed and the worst case complexities associated with are as follows: Multi-objective evolutionary algorithms which uses non-dominated sorting to find pareto front. It is consist of tree parts: • Non-dominated sort returns a list of the non-dominated fronts F. (O(mN 2 )) • Crowding distance assignment is O(mNlogN) • The crowed comparison operator (Sort on ≥ n) guides the selection process at the various stages of the algorithm towards a uniformly spread out Pareto-optimal front. (O(2Nlog(2N)))
Date : 2025-12-28 Size : 5kb User : 罗佳婷
[Other] MOEAFramework-master DL : 0: 多目标进化算法框架，包括MOEAD、NSGA2等经典多目标进化算法。-The MOEA Framework is a free and open source Java library for developing and experimenting with multiobjective evolutionary algorithms (MOEAs) and other general-purpose multiobjective optimization algorithms. The MOEA Framework supports genetic algorithms, differential evolution, particle swarm optimization, genetic programming, grammatical evolution, and more. A number of algorithms are provided out-of-the-box, including NSGA-II, NSGA-III, 蔚-MOEA, GDE3 and MOEA/D. In addition, the MOEA Framework provides the tools necessary to rapidly design, develop, and statistically test optimization algorithms.
Date : 2025-12-28 Size : 14.27mb User : 梁艳芳
[Other] demo4 DL : 0: 遗传算法是计算数学中用于解决最佳化的搜索算法，是进化算法的一种。进化算法最初是借鉴了进化生物学中的一些现象而发展起来的，这些现象包括遗传、突变、自然选择以及杂交等。遗传算法通常实现方式为一种计算机模拟。(Genetic algorithm (GA) is a search algorithm for solving optimization in computational mathematics. It is a kind of evolutionary algorithm. Evolutionary algorithms were originally developed by drawing on some phenomena in evolutionary biology, including inheritance, mutation, natural selection, and hybridization. The genetic algorithm is usually implemented as a computer simulation.)
Date : 2025-12-28 Size : 1kb User : 风12369874
[Other] ypea118-imperialist-competitive-algorithm DL : 0: 所提出的进化优化算法通常是由自然过程建模和物种进化的其他方面，特别是人类进化的启发而得到的。(The proposed evolutionary optimization algorithms are generally inspired by modeling the natural processes and other aspects of species evolution, especially human evolution, are not considered.)
Date : 2025-12-28 Size : 12kb User : SONAH~
[Other] 智能优化算法 DL : 1: 优化技术是一种以数学为基础，用于求解各种工程问题优化解的应用技术。作为一个重要的科学分支，它一直受到人们的广泛重视，并在诸多工程领域得到迅速推广和应用，如系统控制、人工智能、模式识别、生产调度、VLSI技术和计算机工程等。鉴于实际工程问题的复杂性、约束性、非线性、多极小、建模困难等特点，寻求一种适合于大规模并行且具有智能特征的算法已成为有关学科的一个主要研究目标和引人注目的研究方向。 20世纪80年代以来，一些新颖的优化算法，如人工神经网络、混沌、遗传算法、进化。(Optimization technique is an application technique based on mathematics, which is used to solve the optimization problems of various engineering problems. As an important branch of science, it has been paid more and more attention, and has been rapidly popularized and applied in many engineering fields, such as system control, artificial intelligence, pattern recognition, production scheduling, VLSI technology and computer engineering, etc.. In view of the complexity, constraints, nonlinearity, multi minima and modeling difficulties of practical engineering problems, searching for a large-scale parallel and intelligent algorithm has become one of the main research objectives and attractive research directions. Since 1980s, some novel optimization algorithms, such as artificial neural network, chaos, genetic algorithms, evolutionary programming.)
Date : 2025-12-28 Size : 1.93mb User : 韬文
[Other] GA DL : 0: In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on bio-inspired operators such as mutation, crossover and selection.
Date : 2025-12-28 Size : 4kb User : reyhooon
[Other] moead-ira DL : 0: 这是进化算法中常用到的一种算法，moead-ida结合分解和参考点的思想更有利于解决高维多目标问题。(This is an algorithm commonly used in evolutionary algorithms. The idea of combining moead-ida with decomposition and reference points is more conducive to solving high-dimensional multi-objective problems.)
Date : 2025-12-28 Size : 873kb User : hxw
[Other] set DL : 0: 进化优化方法常被用于生成结构化测试用例。现有方法每次仅针对一个被测对象，生一个测试用例。要生成覆盖所有目标的测试用例集，需多次执行进化过程。本文基于集合进化优化方法，实现新的测试用例生成方法。实现的算法中，一个个体包含多个测试用例，因此，一次运行该算法能够生成满足测试需求的测试用例集。(Evolutionary optimization algorithms often used to generate structured test cases. When generating test cases, existing methods generally focus on a target and generate a test case to cover the target. In order to cover all targets, the optimization process must be executed many times. A new method for test case generation is implemented based on set evolution. In the implemented algorithm, a chromosome represents many cases, thus generating a set of test cases which satisfy the testing requirements in a running.)
Date : 2025-12-28 Size : 7kb User : skinner2000
[Other] 2013-TEC-LIPS DL : 0: 进化算法中解决多峰优化问题的经典算法 LIPS(LIPS: A Classical Algorithms for Multi-modal Optimization in Evolutionary Algorithms)
Date : 2019-10-12 Size : 10kb User : 岁寒