Topic
Multi-swarm optimization
About: Multi-swarm optimization is a research topic. Over the lifetime, 19162 publications have been published within this topic receiving 549725 citations.
Papers published on a yearly basis
Papers
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01 Jan 2005
TL;DR: Preliminary experiments show that the BOA outperforms the simple genetic algorithm even on decom posable functions with tight building blocks as a problem size grows.
Abstract: In this paper an algorithm based on the concepts of genetic algorithms that uses an estimation of a probability distribution of promising solutions in order to generate new candidate solutions is proposed To esti mate the distribution techniques for model ing multivariate data by Bayesian networks are used The proposed algorithm identi es reproduces and mixes building blocks up to a speci ed order It is independent of the ordering of the variables in the strings rep resenting the solutions Moreover prior in formation about the problem can be incor porated into the algorithm However prior information is not essential Preliminary ex periments show that the BOA outperforms the simple genetic algorithm even on decom posable functions with tight building blocks as a problem size grows
154 citations
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12 May 2002TL;DR: This paper examines a particle swarm algorithm which has been applied to the generation of interactive, improvised music and suggests that the algorithm may have applications to dynamic optimisation problems.
Abstract: This paper examines a particle swarm algorithm which has been applied to the generation of interactive, improvised music. An important feature of this algorithm is a balance between particle attraction to the centre of mass and repulsive, collision avoiding forces. These forces are not present in the classic particle swarm optimisation algorithms. A number of experiments illuminate the nature of these new forces and it is suggested that the algorithm may have applications to dynamic optimisation problems.
154 citations
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ENEA1
TL;DR: An optimal power dispatch problem on a 24-h basis for distribution systems with distributed energy resources also including directly controlled shiftable loads is presented, using a novel nature-inspired multiobjective optimization algorithm based on an original extension of a glowworm swarm particles optimization algorithm.
Abstract: In this paper, an optimal power dispatch problem on a 24-h basis for distribution systems with distributed energy resources (DER) also including directly controlled shiftable loads is presented. In the literature, the optimal energy management problems in smart grids (SGs) where such types of loads exist are formulated using integer or mixed integer variables. In this paper, a new formulation of shiftable loads is employed. Such formulation allows reduction in the number of optimization variables and the adoption of real valued optimization methods such as the one proposed in this paper. The method applied is a novel nature-inspired multiobjective optimization algorithm based on an original extension of a glowworm swarm particles optimization algorithm, with algorithmic enhancements to treat multiple objective formulations. The performance of the algorithm is compared to the NSGA-II on the considered power systems application.
154 citations
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22 Oct 2007TL;DR: A modified particle swarm optimizer algorithm (MPSO) was presented and the aggregation degree of the particle swarm was introduced to improve the convergence precision and speed of PSO algorithm effectively.
Abstract: This paper presented a modified particle swarm optimizer algorithm (MPSO). The aggregation degree of the particle swarm was introduced. The particles' diversity was improved through periodically monitoring aggregation degree of the particle swarm. On the later development of the PSO algorithm, it has been taken strategy of the Gaussian mutation to the best particle's position, which enhanced the particles' capacity to jump out of local minima. Several typical benchmark functions with different dimensions have been used for testing. The simulation results show that the proposed method improves the convergence precision and speed of PSO algorithm effectively.
154 citations
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TL;DR: This paper introduces a new hybrid method, which employs discrete particle swarm optimization and optimal power flow to overcome this shortcoming in distributed generation systems.
153 citations