A dual sequence simulated annealing algorithm for constrained optimization
MATH'06 Proceedings of the 10th WSEAS International Conference on APPLIED MATHEMATICS
Differential evolution with dynamic stochastic selection for constrained optimization
Information Sciences: an International Journal
Solving nonlinearly constrained global optimization problem via an auxiliary function method
Journal of Computational and Applied Mathematics
C-PSA: Constrained Pareto simulated annealing for constrained multi-objective optimization
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
A fast memoryless interval-based algorithm for global optimization
Journal of Global Optimization
Algorithm 909: NOMAD: Nonlinear Optimization with the MADS Algorithm
ACM Transactions on Mathematical Software (TOMS)
Guided artificial bee colony algorithm
ECC'11 Proceedings of the 5th European conference on European computing conference
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part III
Mixed variable structural optimization using Firefly Algorithm
Computers and Structures
Computers & Mathematics with Applications
Dual sequence simulated annealing with round-robin approach for university course timetabling
EvoCOP'10 Proceedings of the 10th European conference on Evolutionary Computation in Combinatorial Optimization
Multi-agent simulated annealing algorithm based on differential evolution algorithm
International Journal of Bio-Inspired Computation
An artificial fish swarm filter-based method for constrained global optimization
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
A derivative-free filter driven multistart technique for global optimization
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
A penalty function-based differential evolution algorithm for constrained global optimization
Computational Optimization and Applications
Optimum oil production planning using infeasibility driven evolutionary algorithm
Evolutionary Computation
Multilocal programming: a derivative-free filter multistart algorithm
ICCSA'13 Proceedings of the 13th international conference on Computational Science and Its Applications - Volume 1
International Journal of Computing Science and Mathematics
Hi-index | 0.00 |
In this paper, a simulated-annealing-based method called Filter Simulated Annealing (FSA) method is proposed to deal with the constrained global optimization problem. The considered problem is reformulated so as to take the form of optimizing two functions, the objective function and the constraint violation function. Then, the FSA method is applied to solve the reformulated problem. The FSA method invokes a multi-start diversification scheme in order to achieve an efficient exploration process. To deal with the considered problem, a filter-set-based procedure is built in the FSA structure. Finally, an intensification scheme is applied as a final stage of the proposed method in order to overcome the slow convergence of SA-based methods. The computational results obtained by the FSA method are promising and show a superior performance of the proposed method, which is a point-to-point method, against population-based methods.