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A multi-swarm bat algorithm for global optimization
2015 IEEE Congress on Evolutionary Computation (CEC), 2015By simulating the echolocation behavior of bats in nature, bat algorithm (BA) is proposed for global optimization that is a recently developed nature-inspired algorithm. Since then, it has been widely used in various fields. Bat algorithm balance the global search and local search by adjusting loudness and pulse rate. However, there is so many loudness
Gai-Ge Wang, Bao Chang, Zhaojun Zhang
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Symbiotic Multi-swarm PSO for Portfolio Optimization
2009This paper presents a novel symbiotic multi-swarm particle swarm optimization (SMPSO) based on our previous proposed multi-swarm cooperative particle swarm optimization. In SMPSO, the population is divided into several identical sub-swarms and a center communication strategy is used to transfer the information among all the sub-swarms.
Ben Niu, Bing Xue, Li Li, Yujuan Chai
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RFID network planning using a multi-swarm optimizer
Journal of Network and Computer Applications, 2011In this paper, we develop an optimization model for planning the positions of readers in the RFID network based on a novel multi-swarm particle swarm optimizer called PS^2O. The main idea of PS^2O is to extend the single population PSO to the interacting multi-swarms model by constructing hierarchical interaction topology and enhanced dynamical update ...
Hanning Chen +3 more
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Dynamic multi-swarm differential learning particle swarm optimizer
Swarm and Evolutionary Computation, 2018Abstract Because different optimization algorithms have different search behaviors and advantages, hybrid strategy is one of the main research directions to improve the performance of PSO. Inspired by this idea, a dynamic multi-swarm differential learning particle swarm optimizer (DMSDL-PSO) is proposed in this paper.
Yonggang Chen +4 more
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A Multi-Swarm Cooperative Perturbed Particle Swarm Optimization
Advanced Materials Research, 2011Combined with a variety of ideas a Multi-swarm cooperative Perturbed Particle Swarm Optimization algorithm (MpPSO) is presented to improve the performance and to reduce the premature convergence of PSO. This algorithm includes the idea of multiple swarms to improve the evolution efficiency by information sharing between populations to avoid falling ...
Xiang Jun Yang +3 more
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A multi-swarm cooperative hybrid particle swarm optimizer
2010 Sixth International Conference on Natural Computation, 2010Cooperative approaches have proved to be very useful in evolutionary computation. This paper a novel multi-swarm cooperative particle swarm optimization (PSO) is proposed. It involves a collection of two sub-swarms that interact by exchanging information to solve a problem.
Ying Li, Jiaxi Liang, Jie Hu
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Multi-swarms Dynamic Convergence Optimization for object tracking
2016 International Joint Conference on Neural Networks (IJCNN), 2016Swarm intelligence has been applied to many research projects in recent years, many scientists are working on developing the full potential of a self-organized and decentralized system to help solving complex problems. In image processing, it also demonstrates fast and accurate in searching solutions for trajectory clustering and precise object ...
Feng Sha +5 more
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Multi-swarm Particle Grid Optimization for Object Tracking
2016In recent years, one of the popular swarm intelligence algorithm Particle Swarm Optimization has demonstrated to have efficient and accurate outcomes for tracking different object movement. But there are still problems of multiple interferences in object tracking need to overcome.
Feng Sha +4 more
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A Novel Learning Multi-Swarm Particle Swarm Optimization
2023Particle swarm optimization (PSO) is one of the metaheuristic optimization methods. Because of its many advantages, it is often used to solve real-world engineering problems. However, in case of complex, multi-dimensional tasks, PSO faces some problems related to premature conver-gence and stagnation in local optima.
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