Description: 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-objective Evolutionary Algorithm (including SPEA2 and NSGA2), a multi-objective Differential Evolution, a multi-objective Particle Swarm Optimizer (PSO), and a single-objective Simulated Annealing with some predefined cooling schedules. The Opt4J framework also contains several benchmarks like ZDT, DTLZ, or WFG. Platform: |
Size: 1968128 |
Author:stuart |
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Description: Particle swarm optimization (PSO) is a population based stochastic optimization technique developed by Dr. Eberhart and Dr. Kennedy in 1995, inspired by social behavior of bird flocking or fish schooling. Each particle keeps track of its coordinates in the problem space which are associated with the best solution (fitness) it has achieved so far. (The fitness value is also stored.)
This value is called pbest. Another "best" value that is tracked by the particle swarm optimizer is the best value, obtained so far by any particle in the neighbors of the particle. This location is called lbest. when a particle takes all the population as its topological neighbors, the best value is a global best and is called gbest. Following is the steps of PSO:
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Size: 1024 |
Author:BBB |
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Description: PARTICLE SWARM OPTIMIZER IN NOISY AND
CONTINUOUSLY CHANGING ENVIRONMENTS
ABSTRACT
In this paper we study the performance of the recently proposed
Particle Swarm optimization method in the presence
of noisy and continuously changing environments. Experimental
results for well known and widely used optimization
test functions are given and discussed. Conclusions for
its ability to cope with such environments as well as real–
life applications are also derived. Platform: |
Size: 86016 |
Author:dasu |
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Description: 一个桁架结构的动力学响应和主动控制程序，优化算法采用了粒子群方法。仅供参考。-this dissertation discusses the dynamical response and contrlol design of a flexible trussed structure the optimal position of actuator is studied by using the particle swarm optimizer as optimization algorithm. Platform: |
Size: 4096 |
Author:liupan |
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Description: PSO-MATLAB-CODE
This code is about an objective particle swarm optimizer with emphasis on efficiency
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Size: 4982784 |
Author:daneshmandmitra |
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Description: PARTICLE SWARM OPTIMIZER AND SOME BENCHMARK PROBLEM FOR GLOBAL OPTIMIZATION ALGORTIRHMS, IMPLEMENTED IN MATLAB DIM, LOW AND UP LIMITS CAN BE FOUND IN RELATED FILE Platform: |
Size: 43008 |
Author:INANKAAN |
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Description: In implementing this project, four types of gray wolves like Alpha, Beta, Delta and Omega is the use to simulate the leadership hierarchy in which the three main steps of the hunt, searching for prey, surrounded prey, and attack the bait, are implemented. The simulation results with particle swarm algorithm (PSO) is compared, show that the algorithm has achieved better performance Grey Wolf GWO. Platform: |
Size: 1938432 |
Author:scada111 |
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