Particle swarm with speciation and adaptation in a dynamic environment
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Multi-strategy ensemble particle swarm optimization for dynamic optimization
Information Sciences: an International Journal
A Generalized Approach to Construct Benchmark Problems for Dynamic Optimization
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
A memetic algorithm with adaptive hill climbing strategy for dynamic optimization problems
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Emerging Trends in Soft Computing - Memetic Algorithms; Guest Editors: Yew-Soon Ong, Meng-Hiot Lim, Ferrante Neri, Hisao Ishibuchi
A study on diversity and cooperation in a multiagent strategy for dynamic optimization problems
International Journal of Intelligent Systems - Special Issue on Nature Inspired Cooperative Strategies for Optimization
Controlling Particle Trajectories in a Multi-swarm Approach for Dynamic Optimization Problems
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part I: Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira's Scientific Legacy
Performance Analysis of MADO Dynamic Optimization Algorithm
ISDA '09 Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
Unidimensional Search for Solving Continuous High-Dimensional Optimization Problems
ISDA '09 Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
The differential ant-stigmergy algorithm applied to dynamic optimization problems
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Dynamic optimization using self-adaptive differential evolution
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A dynamic artificial immune algorithm applied to challenging benchmarking problems
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Evolutionary programming with ensemble of explicit memories for dynamic optimization
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A clustering particle swarm optimizer for dynamic optimization
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Particle swarm optimization with composite particles in dynamic environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Evolutionary optimization in uncertain environments-a survey
IEEE Transactions on Evolutionary Computation
Locating and tracking multiple dynamic optima by a particle swarm model using speciation
IEEE Transactions on Evolutionary Computation
Multiswarms, exclusion, and anti-convergence in dynamic environments
IEEE Transactions on Evolutionary Computation
Population-Based Incremental Learning With Associative Memory for Dynamic Environments
IEEE Transactions on Evolutionary Computation
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Many real-world optimization problems are dynamic (time dependent) and require an algorithm that is able to track continuously a changing optimum over time. In this paper, we propose a new algorithm for dynamic continuous optimization. The proposed algorithm is based on several coordinated local searches and on the archiving of the optima found by these local searches. This archive is used when the environment changes. The performance of the algorithm is analyzed on the Moving Peaks Benchmark and the Generalized Dynamic Benchmark Generator. Then, a comparison of its performance to the performance of competing dynamic optimization algorithms available in the literature is done. The obtained results show the efficiency of the proposed algorithm.