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Symbiosis-Based Alternative Learning Multi-Swarm Particle Swarm Optimization
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2017Inspired by the ideas from the mutual cooperation of symbiosis in natural ecosystem, this paper proposes a new variant of PSO, named Symbiosis-based Alternative Learning Multi-swarm Particle Swarm Optimization (SALMPSO). A learning probability to select one exemplar out of the center positions, the local best position, and the historical best position ...
Ben Niu +3 more
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Multi-swarm Optimization with Chaotic Mapping for Dynamic Optimization Problems
2015 8th International Symposium on Computational Intelligence and Design (ISCID), 2015In real-world applications, many optimization problems are dynamic, therefore the goal of optimization algorithms is not only to obtain the optimal solution, but also to have strong adaptive capability to the environment changes and track the trajectory of the optimal solution as closely as possible.
Luyi Shen +3 more
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Multi-swarm optimization algorithm for dynamic optimization problems using forking
2008 Chinese Control and Decision Conference, 2008Inspired by a forking mechanism, a new multi-swarm optimization algorithm is proposed for addressing dynamic optimization problems in this paper. In this algorithm, a larger main swarm is continuously responsible for searching for new peaks and a number of smaller child swarm, divided from main swarm, are used to track the achieved peaks over time ...
null Hongfeng Wang +2 more
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Fully Learned Multi-swarm Particle Swarm Optimization
2014This paper presents a new variant of PSO, called fully learned multi-swarm particle swarm optimization (FLMPSO) for global optimization. In FLMPSO, the whole population is divided into a number of sub-swarms, in which the learning probability is employed to influence the exemplar of each individual and the center position of the best experience found ...
Ben Niu +4 more
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Cooperative Multi-Swarms Particle Swarm Optimizer for dynamic environment optimization
2008 27th Chinese Control Conference, 2008Optimization problem in the dynamic environment is not only to locate a optimum, but track the moving optimum as close as possible. Particle swarm optimizer, a kind parallel random optimization method based on swarm intelligence, exhibits good performance for optimization problem.
null Wang Guang-Hui +2 more
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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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Multi swarm optimization algorithm with adaptive connectivity degree
Applied Intelligence, 2017Particle swarm optimization algorithms are very sensitive to their population topologies. In all PSO variants, each particle adjusts it flying velocity according to a set of attractor particles. The cardinality of this set is a feature of neighborhood topology.
Reza Vafashoar, Mohammad Reza Meybodi
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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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