Simulated annealing: theory and applications
Simulated annealing: theory and applications
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
How to solve it: modern heuristics
How to solve it: modern heuristics
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Journal of Global Optimization
Genetic AlgorithmsNumerical Optimizationand Constraints
Proceedings of the 6th International Conference on Genetic Algorithms
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Opposition-Based Learning: A New Scheme for Machine Intelligence
CIMCA '05 Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-1 (CIMCA-IAWTIC'06) - Volume 01
Fundamentals of Computational Swarm Intelligence
Fundamentals of Computational Swarm Intelligence
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Differential evolution and non-separability: using selective pressure to focus search
Proceedings of the 9th annual conference on Genetic and evolutionary computation
A Novel Opposition-Based Particle Swarm Optimization for Noisy Problems
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 03
Differential evolution algorithm with strategy adaptation for global numerical optimization
IEEE Transactions on Evolutionary Computation
Differential evolution using a neighborhood-based mutation operator
IEEE Transactions on Evolutionary Computation
Free Search-a comparative analysis
Information Sciences: an International Journal
A study of particle swarm optimization particle trajectories
Information Sciences: an International Journal
JADE: adaptive differential evolution with optional external archive
IEEE Transactions on Evolutionary Computation
Self-adaptive differential evolution
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
IEEE Computational Intelligence Magazine
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Chaotic sequences to improve the performance of evolutionary algorithms
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Opposition-Based Differential Evolution
IEEE Transactions on Evolutionary Computation
A novel particle swarm optimization algorithm with adaptive inertia weight
Applied Soft Computing
Survey A review of opposition-based learning from 2005 to 2012
Engineering Applications of Artificial Intelligence
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CODEQ is a new, parameter-free meta-heuristic algorithm that is hybrid of concepts from chaotic search, opposition-based learning, differential evolution (DE) and quantum mechanics. The performance of the proposed approach is investigated and compared with other well-known population-based optimisation approaches when applied to solve 19 benchmark functions. The conducted experiments show that CODEQ presents excellent results with almost no parameter tuning. Moreover, the performance of CODEQ when applied to high-dimensional problems is investigated with excellent results. Finally, the application of CODEQ to constrained and real-world engineering problems is investigated with encouraging results.