一、背景知识(1)起源1995年,受到鸟群觅食行为的规律性启发,James Kennedy和Russell Eberhart建立了一个简化算法模型,经过多年改进最终形成了 粒子群优化算法(Particle Swarm Optimization, PSO) ,也可称为粒…
A particle swarm optimization algorithm is a simple optimization algorithm used for a variety of functions, discovered through a social model simulation. It is applied in image processing and feature extraction to reduce computation complexity and improve efficiency compared to other algorithms like the ...
To improve the overall performance of the particle swarm algorithm, an improved particle swarm optimization algorithm is proposed by the multiple hybrid strategy in this paper. The improved PSO incorporates the search ideas of other intelligent algorithms (DE, WOA), so the improved algorithm proposed...
Particle swarm optimization is used for problems where the function to be optimized is discontinuous, non-differentiable with too many non-linearly related parameters (Floreano & Mattiussi, 2008). These algorithms operates in a sequence of few iterative steps defined on the behaviour of the organism...
The primary motivation of this work is to explore and improve particle swarm optimization (PSO) techniques for multi-objective (MO) function optimization as well as to expand its applications in real world bin packing problems. Information from this study would help people better understand PSO ...
此外,进化算法(Evolutionary Algorithms,EAs),如遗传算法(Genetic Algorithms,GAs)[13,23]、差分进化(Differential Evolution,DE)[8,35]和粒子群优化(Particle Swarm Optimization,PSO)算法[32,48]因其优越的搜索性能而被广泛应用于FS。单目标EAs可以通过将两个目标聚合为一个目标来解决多目标FS问题,这需要大量的领域...
Algorithms For a description of the particle swarm optimization algorithm, see Particle Swarm Optimization Algorithm. Alternative Functionality App The Optimize Live Editor task provides a visual interface for particleswarm. Extended Capabilities expand all Automatic Parallel Support Accelerate code by automatic...
A survey on particle swarm optimization algorithms for multimodal function optimization - Liu, Ling, et al. - 2011 () Citation Context ...ic and engineering optimizationsproblems are highly multimodal, i.e. multiple global optimasexist; therefore, it is often desirable to locate either all or ...
This is the first book devoted entirely to Particle Swarm Optimization (PSO), which is a non-specific algorithm, similar to evolutionary algorithms, such as taboo search and ant colonies. Since its original development in 1995, PSO has mainly been
modifying the initialization process of the swarm; combining with other intelligent algorithms. To improve the overall performance of the particle swarm algorithm, a modified particle swarm optimization (MPSO) is proposed for solving the multiple constraints and NP-hard vehicle scheduling problem. The MP...