id: 06045835
dt: j
an: 06045835
au: Shieh, Horng-Lin; Kuo, Cheng-Chien; Chiang, Chin-Ming
ti: Modified particle swarm optimization algorithm with simulated annealing
    behavior and its numerical verification.
so: Appl. Math. Comput. 218, No. 8, 4365-4383 (2011).
py: 2011
pu: Elsevier Science Publishing Co. (North-Holland), New York
la: EN
cc: 
ut: simulated annealing; particle swarm optimization; heuristic search;
    Metropolis process; elite reserve; algorithm; stochastic optimization;
    convergence
ci: 
li: doi:10.1016/j.amc.2011.10.012
ab: Summary: A hybrid algorithm that combined particle swarm optimization with
    simulated annealing behavior (SA-PSO) is proposed. The SA-PSO algorithm
    takes both of the advantages of good solution quality in simulated
    annealing and fast searching ability in particle swarm optimization. As
    stochastic optimization algorithms are sensitive to their parameters,
    proper procedure for parameters selection is introduced in this paper
    to improve solution quality. To verify the usability and effectiveness
    of the proposed algorithm, simulations are performed using 20 different
    mathematical optimization functions with different dimensions. The
    comparative works have also been conducted among different algorithms
    under the criteria of quality of the solution, the efficiency of
    searching for the solution and the convergence characteristics.
    According to the results, the SA-PSO could have higher efficiency,
    better quality and faster convergence speed than compared algorithms.
rv: