Description: 一种新型带有约束条件的标准粒子群算法，小弟第一次上传，还请各位大哥多多帮助和支持！-A new type of constraint condition with the standard particle swarm optimization,小弟From the first time, also please a lot of help and support older brother! Platform: |
Size: 2048 |
Author:毛毛 |
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Description: 用于分析带约束问题的输出结果,加上约束的粒子群算法功能有很大改善-Used to analyze the problem with constraint output, coupled with constrained particle swarm optimization function has greatly improved Platform: |
Size: 2048 |
Author:jiangzhiling |
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Description: 一个基于阈值的粒子比较准则，用于处理多目标约束优化问题,该准则可以保留一部分序值较小且约束违反度在允许范围内的不可行解微粒,从而达到由不可行解向可行解进化的目的；一个新的拥挤度函数,使得位于稀疏区域和Pareto前沿边界附近的点有较大的拥挤度函数值,从而被选择上的概率也较大 从而构成解决多目标约束优化问题的混合粒子群算法。-A comparison based on the threshold criteria for the particle to handle multi-objective constrained optimization problem, part of the guidelines can keep order value is small and the constraint violation in allowing infeasible solutions within the particles, so as to achieve a feasible solution to the infeasible solution The purpose of evolution a new function of crowding, making the Pareto front in the sparse region and near the border points have a greater value of the congestion function, which is the larger the probability of selection so as to constitute solve multi-objective constrained optimization problems hybrid particle swarm algorithm. Platform: |
Size: 4096 |
Author:李洪 |
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Description: 用粒子群算法求解单一水库优化调度，只需要修改相应的约束条件就可以进行优化计算了-With a single particle swarm algorithm is optimizing reservoir operation, only need to modify the corresponding constraint conditions can were optimized
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Size: 3072 |
Author: |
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Description: 针对工程优化设计问题,提出了基于混沌粒子群算法的工程约束优化问题求解方法。CPSO算法利用混沌搜
索的全局遍历性、随机性和规律性等特点, 引导粒子在全局范围内搜索, 从而克服了传统粒子群算法早熟收敛的缺点。
该算法以种群适应度方差作为粒子群优化算法早熟收敛的判据, 并用惩罚函数法处理违法约束的粒子, 当基本粒子群算
法陷入早熟时, 随机选择粒子群中的部分粒子实施混沌搜索, 直至满足迭代收敛条件为止。CPSO算法能提高种群的多
样性和粒子搜索的遍历性, 从而有效提高了PSO算法的收敛速度和精度。两个工程约束优化实例的求解结果表明,该算
法的优化结果最好, 收敛速度也比较快-Based on engineering design optimization problems, and put forward based on chaotic particle swarm optimization algorithm of engineering problem solving methods. CPSO algorithm by using chaos search
The global ergodicity, stochastic characteristics and regularity, and lead particles in the global scope search, and overcome the traditional particle swarm algorithm premature convergence faults.
In this algorithm, the population fitness variance as the particle swarm optimization algorithm of the criterion of premature convergence, the penalty function method and deal with illegal constraint particles, when basic particle swarm to calculate
Law in early maturity, random selection of particle swarm of these particles implementation chaotic search, until the convergence conditions meet so far. CPSO algorithm can improve the population
Sample sex and particles of searching ergodicity, thus effectively improved PSO algorithm convergence speed and accuracy. Two engineering constraint optim Platform: |
Size: 745472 |
Author:吴胜亮 |
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Description: 基本的粒子群优化算法，对于粒子的速度和位置进行了约束，适合新手学习-The basic particle swarm optimization algorithm, the particle velocity and position constraint for beginners to learn Platform: |
Size: 4096 |
Author:jihai77007 |
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Description: 求解0-1二次规划的粒子群算法
先将离散的0-1变量约束转化成了不光滑方程的约束，再用磨光函数方法对其光滑化。最终，把原来的数学模型转化为可微的非线性规划问题。最后，粒子群优化算法求解-0-1 first discrete particle swarm algorithm for solving 0-1 quadratic programming variable constraint transformed into smooth equations and constraints, its smoothing function method and then polished. Eventually, the original mathematical model into differentiable nonlinear programming problem. Finally, the particle swarm optimization algorithm Platform: |
Size: 2048 |
Author:sandy |
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Description: 粒子群优化算法的寻优算法，以求解约束条件下的极大值-Particle swarm optimization algorithm and optimization algorithm, to solve the constraint conditions of maximum Platform: |
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Author:文东杰 |
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Description: 粒子群优化工具箱，采用Matlab编写的PSO程序工具箱-Development Notes for psopt toolbox
Future plans (in no particular order):
* Performance improvement: Automatically check for existence of constraints, skip boundary-checking if unconstrained.
* Performance improvement: Automatically vectorize fitness functions supplied by user, if not already vectorized.
* Performance improvement: Detect and eliminate dependent (i.e. redundant) linear constraints.
* Performance improvement: Automatically choose "penalize" versus "soft" constraint handling method based on type of constraints in problem. If any equality constraints exist, using "penalize", otherwise default to "soft". If "soft", automatically switch to "penalize" if more than a given percentage of particles (initial or interim) are infeasible.
* Feature: An output function defined by options.OutputFcns that can save current swarm state in a file which can be reloaded later as a problem structure, in case of a system crash.
* Feature: Implement multiobjective optimization option Platform: |
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Author:张绍良 |
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Description: Parsopoulos等采用罚函数法，利用非固定多段映射函数对约束优化问题进行转化，再利用PSO算法求解转化后问题，仿真结果显示PSO算法相对遗传算法更具有优越性，但其罚函数的设计过于复杂，不利于求解；Hu等采用可行解保留政策处理约束，即一方面更新存储中所有粒子时仅保留可行解，另一方面在初始化阶段所有粒子均从可行解空间取值，然而初始可行解空间对于许多问题是很难确定的；Ray等提出了具有多层信息共享策略的粒子群原理来处理约束，根据约束矩阵采用多层Pareto排序机制来产生优良粒子，进而用一些优良的粒子来决定其余个体的搜索方向。
-Parsopoulos etc. penalty function method, the use of non-fixed multi-stage mapping function constrained optimization problem for transformation, reuse PSO algorithm for solving the problem after the conversion, the simulation results show that the relative genetic algorithm PSO algorithm has more advantages, but its design is too complicated penalty function is not conducive to solving Hu retention policies such as the use of feasible solutions processing constraints, on the one hand to retain only feasible solution when updating the store all particles, on the other hand all the particles are in the initialization phase values from the feasible solution space, however, the initial feasible solution space For many the problem is difficult to determine Ray and put forward the principle of a multi-layer particle swarm information sharing strategies to deal with constraints, according to the constraint matrix using multi Pareto superior sorting mechanism to generate partic Platform: |
Size: 2048 |
Author:朱坤鸿 |
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Description: 用多目标粒子群优化来求解多目标优化问题，该方法可求解各种多目标问题。程序内包含多种测试函数，和适应度函数求解程序及目标函数和约束函数的具体程序说明。-Multi-objective particle swarm optimization to solve the multi-objective optimization problem which can be solved a variety of multi-objective problem. Specific procedures within the program includes a variety of test functions, and fitness function solver and objective function and constraint functions described. Platform: |
Size: 8192 |
Author:雪缦 |
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Description: 用粒子群算法处理带约束问题，处理约束条件使用的是罚函数法，代码中附有中文注释，txstA.txt文件是约束函数的系数组成的矩阵(Particle swarm algorithm is applied to deal with the constrained problem. The penalty function is applied to deal with the constraint condition. The code is accompanied by Chinese annotation. The txstA.txt file is the matrix of the constraint function's coefficient.) Platform: |
Size: 2048 |
Author:matlab彻 |
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Description: 含有约束方程 求最值所用的罚函数+粒子群优化算法(Penalty function + particle swarm optimization algorithm for using the constraint equation to find the maximum value) Platform: |
Size: 1024 |
Author:eddy54 |
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Description: 该资源使用matlab编写的有约束条件的粒子群算法，其中的代码对于解决一些约束问题可能会有很大的帮助，也可以为一些人提供一些想法与思路(This resource uses a constrained particle swarm algorithm written in matlab. The code in it may be very helpful for solving some constraint problems, and it can also provide some people with some ideas and ideas) Platform: |
Size: 1280000 |
Author:修道人 |
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Search - Particle Swarm constraint