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Energy efficient transactions for blockchain networks using adaptive global best-worst particle swarm optimization. [PDF]

Sci Rep
Jhariya MK, Dehalwar V, Bharti J, Kumar L.   +3 more
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Numerical Optimization and Experimental Validation of Finite Perforated Cellular Panels for Vibration Reduction. [PDF]

Materials (Basel)
Sáez B, Meruane V, Fernández R, Saavedra Flores EI.   +3 more
europepmc   +1 more source

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Particle swarm optimization (PSO). A tutorial

Chemometrics and Intelligent Laboratory Systems, 2015
Abstract Swarm-based algorithms emerged as a powerful family of optimization techniques, inspired by the collective behavior of social animals. In particle swarm optimization (PSO) the set of candidate solutions to the optimization problem is defined as a swarm of particles which may flow through the parameter space defining trajectories which are ...
MARINI, Federico, Walczak, Beata
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Frankenstein's PSO: A Composite Particle Swarm Optimization Algorithm

IEEE Transactions on Evolutionary Computation, 2009
During the last decade, many variants of the original particle swarm optimization (PSO) algorithm have been proposed. In many cases, the difference between two variants can be seen as an algorithmic component being present in one variant but not in the other.
Montes De Oca Roldan, Marco, Stützle, Thomas, Birattari, Mauro, Dorigo, Marco   +3 more
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Particle Swarm Optimization (PSO) for the constrained portfolio optimization problem

Expert Systems with Applications, 2011
One of the most studied problems in the financial investment expert system is the intractability of portfolios. The non-linear constrained portfolio optimization problem with multi-objective functions cannot be efficiently solved using traditionally approaches.
Zhu, Hanhong, Wang, Yi, Wang, Kesheng, Chen, Yun   +3 more
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The gregarious particle swarm optimizer (G-PSO)

Proceedings of the 8th annual conference on Genetic and evolutionary computation, 2006
This paper presents a gregarious particle swarm optimization algorithm (G-PSO) in which the particles explore the search space by aggressively scouting the local minima with the help of only social knowledge. To avoid premature convergence of the swarm, the particles are re-initialized with a random velocity when stuck at a local minimum.
Battiti, Roberto, Pasupuleti, Srinivas
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Parallelizing a Modified Particle Swarm Optimizer (PSO)

Advanced Materials Research, 2010
Recently, a modified Particle Swarm Optimizer (MLPSO) has been succeeded in solving truss topological optimization problems and competitive results are obtained. Since this optimizer belongs to evolutionary algorithm and plagued by high computational cost as measured by execution time, in order to reduce its execution time for solving large complex ...
Bin Yang, Qi Lin Zhang
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