Modified particle swarm optimization algorithm with simulated annealing behavior and its numerical verification

DOI10.1016/j.amc.2011.10.012zbMath1244.65088OpenAlexW2096688831MaRDI QIDQ426984

Chin-Ming Chiang, Horng-Lin Shieh, Cheng-Chien Kuo

Publication date: 13 June 2012

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2011.10.012

zbMATH Keywords

algorithmconvergencestochastic optimizationsimulated annealingheuristic searchparticle swarm optimizationelite reserveMetropolis process

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Stochastic programming (90C15) Combinatorial optimization (90C27)

Related Items (7)

On the improvement of the parameter estimation of the grey model GM(1,1) and model application ⋮ Improved particle swarm optimizer for problems with variable evaluation time: Application to asymptotic homogenization ⋮ Adaptive differential evolution with a Lagrange interpolation argument algorithm ⋮ Reinforcement radial basis function neural networks with an adaptive annealing learning algorithm ⋮ LGMS-FOA: an improved fruit fly optimization algorithm for solving optimization problems ⋮ An improved particle swarm optimization algorithm based on centroid and exponential inertia weight ⋮ Heuristic algorithms for the single allocation \(p\)-hub center problem with routing considerations

Cites Work

• Optimization by Simulated Annealing
• Investigation of temperature parallel simulated annealing for optimizing continuous functions with application to hyperspectral tomography
• Designing an efficient method for tandem AGV network design problem using tabu search
• A new genetic algorithm for solving nonconvex nonlinear programming problems
• Application of particle swarm optimization for distribution feeder reconfiguration considering distributed generators
• A simulated annealing technique for multi-objective simulation optimization
• Iterated tabu search for the maximum diversity problem
• Stochastic optimization using simulated annealing with hypothesis test
• Convergence properties of simulated annealing for continuous global optimization
• Convergence and finite-time behavior of simulated annealing
• Equation of State Calculations by Fast Computing Machines

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