Search - local search algorithm

Search - local search algorithm - List

[Other] njuton DL : 0: optimization algorithm search local minimum function, very quick
Date : 2026-01-02 Size : 16kb User : zerket
[Other] TSP DL : 0: 　提出一种改进的禁忌搜索算法来求解背包问题。该算法基于禁忌搜索技术,并采用I&D策略,同时设计了两种针对局部最优解的变异算子。改进后的算法能有效地弥补标准禁忌算法对初始解依赖的缺陷,同时也避免了搜索停滞的现象。通过对具体实例和随机问题的测试,表明改进后的禁忌搜索算法有更好的性能。关-An improved tabu search algorithm to solve knapsack problem. The algorithm is based on tabu search techniques, using I & D strategies, while designed for the local optimal solution of the two kinds of mutation operator. The improved algorithm can effectively compensate for the standard tabu search algorithm depends on the initial solution defect, but also to avoid the phenomenon of search stagnation. Through specific examples and random-question test, indicating that the improved tabu search algorithm has better performance. Guan
Date : 2026-01-02 Size : 6kb User : logspace
[Other] 05363793 DL : 0: An Improved PSO Algorithm to Optimize BP Neural Network Abstract This paper presents a new BP neural network algorithm which is based on an improved particle swarm optimization (PSO) algorithm. The improved PSO (which is called IPSO) algorithm adopts adaptive inertia weight and acceleration coefficients to significantly improve the performance of the original PSO algorithm in global search and fine-tuning of the solutions. This study uses the IPSO algorithm to optimize authority value and threshold value of BP nerve network and IPSO-BP neural network algorithm model has been established. The results demonstrate that this model has significant advantages inspect of fast convergence speed, good generalization ability and not easy to yield minimal local results
Date : 2026-01-02 Size : 247kb User : dasu
[Other] 01178808 DL : 0: Simulated Annealing With Local Search—A Hybrid Algorithm for Unit Commitment
Date : 2026-01-02 Size : 117kb User : power
[Other] Parallel-genetic-algorithm DL : 0: 经典遗传算法利用单一种群对种群个体进行交叉、变异和选择操作，在进化过程中的超级个体易产生过早收敛现象，粗粒度并行遗传算法利用多个子种群进行进化计算，各子群体分别独立进行遗传操作，相互交换最优个体后继续进化。该文证明了该算法的搜索过程是一个有限时齐遍历马尔柯夫链，给出粗粒度并行遗传算法全局最优收敛性证明。对于旅行商问题TSP利用粗粒度并行遗传算法进行了求解，以解决经典遗传算法的收敛到局部最优值问题。仿真结果表明，算法的收敛性能优于经典遗传算法。-Classic genetic algorithm using a single population of individuals in a population cross, mutation and selection operation, the super individuals in the evolutionary process is easy to produce premature convergence phenomenon, coarse-grained parallel genetic algorithm using multiple sub-populations of evolutionary computation, various sub-groups, respectively, independent The genetic manipulation, the exchange of best individual continue to evolve. This paper shows that the search process of the algorithm is a finite homogeneous traverse the Markov chain, given the coarse-grained parallel genetic algorithm global optimal convergence proof. For the traveling salesman problem TSP coarse-grained parallel genetic algorithm to solve to solve the classic genetic algorithm converges to a local optimum value. The simulation results show that the convergence of the algorithm is superior to the classical genetic algorithm.
Date : 2026-01-02 Size : 910kb User : 陈嘉鑫
[Other] DE-demo DL : 0: 微分进化算法是一种非常重要的参数寻有选择算法，可以有效的选择一些控制算法参数。-The differential evolution algorithm to search the global optimal solution of the stochastic optimization algorithm is an analog of the natural biological evolution. Because the differential evolution algorithm is simple and easy to implement less control parameters and search ability has been extensive research and application. And other population-based evolutionary algorithm, differential evolution algorithm there are also some shortcomings, mainly in the lack of premature convergence and local search ability.
Date : 2026-01-02 Size : 1kb User : 许巍
[Other] grasp DL : 0: GRASP (greedy randomized adaptive search Procedure) is an algorithm commonly applied to problems of combinatorial optimization. As various construction methods, the application of grasp is to create an initial solution and then perform a local search to improve the quality of the solution. Your differential to other methods is the generation of initial solution, based on the first three stages of its acronym in English: greedy (Greedy), random (trial) and adaptive (Adaptive).
Date : 2026-01-02 Size : 1kb User : wesleymagasat
[Other] 蛙跳程序 DL : 0: 蛙跳算法（SFLA）是一种全新的启发式群体进化算法，具有高效的计算性能和优良的全局搜索能力。对混合蛙跳算法的基本原理进行了阐述，针对算法局部更新策略引起的更新操作前后个体空间位置变化较大，降低收敛速度这一问题，提出了一种基于阈值选择策略的改进蛙跳算法。通过不满足阈值条件的个体分量不予更新的策略，减小了个体空间差异，从而改善了算法的性能。数值实验证明了该改进算法的有效性，并对改进算法的阈值参数进行了率定。(Leapfrog algorithm (SFLA) is a new heuristic population evolutionary algorithm, has high computing performance and excellent global search ability. The basic principle of SFLA is discussed, and the update operation algorithm based on local updating strategy caused by the change of individual space greatly, reduce the speed of convergence of this problem, proposed an improved shuffled frog leaping algorithm based on the threshold selection strategy. By reducing the individual variance of the individual components without satisfying the threshold condition, the performance of the algorithm is improved. Numerical experiments demonstrate the effectiveness of the improved algorithm and determine the threshold parameters of the improved algorithm.)
Date : 2026-01-02 Size : 1kb User : xdw0421
[Other] TS DL : 0: 禁忌搜索算法源代码，对局部邻域搜索的一种扩展，搜索过程中采用禁忌准则，即不考虑处于禁忌状态的解，标记对应已搜索的局部最优解的一些对象，在进一步迭代搜索中尽量避开这些对象，避免迂回搜索，从而保证对不同的有效搜索途径的检索，是一种局部极小突跳的全局逐步寻优算法。(Tabu search algorithm source code, an extension of the local neighborhood search criteria, using tabu search process, that is not considered a taboo in state solution, some local optimal search object mark corresponding solutions, avoid these objects as far as possible in the further iterative search, avoid circuit search, so as to ensure the effective way to search search different, is a local minimum jump global stepwise optimization algorithm.)
Date : 2026-01-02 Size : 12kb User : 进步小青年儿
[Other] 智能优化算法资料 DL : 0: 优化算法有很多，经典算法包括：有线性规划，动态规划等；改进型局部搜索算法包括爬山法，最速下降法等，模拟退火、遗传算法以及禁忌搜索称作指导性搜索法。而神经网络，混沌搜索则属于系统动态演化方法。梯度为基础的传统优化算法具有较高的计算效率、较强的可靠性、比较成熟等优点，是一类最重要的、应用最广泛的优化算法。但是，传统的最优化方法在应用于复杂、困难的优化问题时有较大的局限性。(There are many optimization algorithms, the classical algorithms include linear programming, dynamic programming, etc. the improved local search algorithms include hill-climbing method, steepest descent method, etc. simulated annealing, genetic algorithm and tabu search are called the guiding search methods. The neural network and chaotic search belong to the dynamic evolution method of the system. Gradient based traditional optimization algorithm has the advantages of high computational efficiency, strong reliability and relatively mature. It is one of the most important and most widely used optimization algorithms. However, the traditional optimization method has great limitations when it is applied to complex and difficult optimization problems.)
Date : 2026-01-02 Size : 1.77mb User : 韬文
[Other] taceTrab1JenesInteiro DL : 0: The Michalewicz function has d! local minima, and it is multimodal. The parameter m defines the steepness of they valleys and ridges; a larger m leads to a more difficult search.
Date : 2026-01-02 Size : 708kb User : edjalma
[Other] 基于最优流的配电网络重构程序 DL : 1: 提出了一种基于改进最优流和遗传算法的配电网重构算法.该算法先利用配电网的同胚图将重构问题的全局寻优空间划分为若干子空间,然后利用改进最优流法寻找子空间内的最优解,之后再利用遗传算法搜索全局最优解所在的子空间,从而实现在局部最优解中寻找全局最优解.(A distribution network reconfiguration algorithm based on improved optimal flow and genetic algorithm is proposed. First, the global optimization space of the reconfiguration problem is divided into several subspaces by using the homeomorphic graph of the distribution network. Then, the improved optimal flow method is used to find the optimal solution in the subspace. Then, the genetic algorithm is used to search the subspace where the global optimal solution is located, so as to find the global optimal solution in the local optimal solution. The optimal solution.)
Date : 2026-01-02 Size : 1kb User : 东北大成子
[Other] 蚁群算法 DL : 0: 本文对蚁群算法的基本理论以及在 TSP 问题中的应用进行了系统研究和 MATLAB 仿真。介绍了蚁群算法的基本原理、特点和算法的实现方法。.基本蚁群算法由于存在搜索时间长，易陷入局部最优解等突出缺点，使得求解效果不是很好。针对这些缺陷，提出了改进的蚁群算法（最大-最小蚂蚁系统）求解 TSP 问题。改进主要在于限制路径信息素浓度、信息素的初始值以及强调对最优解得利用这三个方面。(In this paper, the basic theory of ant colony algorithm and its application in TSP are studied systematically and simulated by MATLAB. This paper introduces the basic principle, characteristics and implementation of ant colony algorithm. The basic ant colony algorithm is not very good because of its long search time and easy to fall into the local optimal solution. Aiming at these defects, an improved ant colony algorithm (maximum minimum ant system) is proposed to solve TSP. The main improvements are to limit the concentration of pheromone, the initial value of pheromone and to emphasize the utilization of the optimal solution.)
Date : 2026-01-02 Size : 6kb User : 阳光1111111