Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
Real-valued genetic algorithms for fuzzy grey prediction system
Fuzzy Sets and Systems
Improved genetic operators for structural engineering optimization
Advances in Engineering Software
Genetic learning of fuzzy controllers
Mathematics and Computers in Simulation
Optimization of fuzzy rules design using genetic algorithm
Advances in Engineering Software
Vector quantization based on genetic simulated annealing
Signal Processing
Combining mutation operators in evolutionary programming
IEEE Transactions on Evolutionary Computation
An orthogonal genetic algorithm with quantization for globalnumerical optimization
IEEE Transactions on Evolutionary Computation
An introduction to simulated evolutionary optimization
IEEE Transactions on Neural Networks
Damage detection by an adaptive real-parameter simulated annealing genetic algorithm
Computers and Structures
Engineering Applications of Artificial Intelligence
Virus coevolution partheno-genetic algorithms for optimal sensor placement
Advanced Engineering Informatics
Expert Systems with Applications: An International Journal
A novel clustering algorithm based on the extension theory and genetic algorithm
Expert Systems with Applications: An International Journal
A flexible tolerance genetic algorithm for optimal problems with nonlinear equality constraints
Advanced Engineering Informatics
Fusion of multi-focus images using differential evolution algorithm
Expert Systems with Applications: An International Journal
Intelligent bionic genetic algorithm (IB-GA) and its convergence
Expert Systems with Applications: An International Journal
An enhanced GA technique for system training and prognostics
Advances in Engineering Software
Mixed variable structural optimization using Firefly Algorithm
Computers and Structures
Accelerating fuzzy genetic algorithm for the optimization of steel structures
Structural and Multidisciplinary Optimization
Fault diagnosis of analog circuits using extension genetic algorithm
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
A distributed agent-based approach for simulation-based optimization
Advanced Engineering Informatics
Collaboration and Competition Process: A Multi-Teams and Genetic Algorithm Hybrid Approach
International Journal of Artificial Life Research
A framework for evolutionary algorithms based on Charles Sanders Peirce's evolutionary semiotics
Information Sciences: an International Journal
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One drawback of genetic algorithm is that it may spend much computation time in the encoding and decoding processes. Also, since genetic algorithm lacks hill-climbing capacity, it may easily fall in a trap and find a local minimum not the true solution. In this paper, a novel adaptive real-parameter simulated annealing genetic algorithm (ARSAGA) that maintains the merits of genetic algorithm and simulated annealing is proposed. Adaptive mechanisms are also included to insure the solution quality and to improve the convergence speed. The performance of the proposed operators has been discussed in detail and compared to other operators, and the performance of the proposed algorithm is demonstrated in 16 benchmark functions and two engineering optimization problems. Due to their versatile characteristics, these examples are suitable to test the ability of the proposed algorithm. The results indicate that the global searching ability and the convergence speed of this novel hybrid algorithm are significantly better, even though small population size is used. Also, the proposed algorithm has good application to engineering optimization problems. Hence, the proposed algorithm is efficient and improves the drawbacks of genetic algorithm.