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All Outputs (4)

Collaboration of heterogenous metaheuristic agents (2010)
Conference Proceeding
Aydin, M. E. (2010). Collaboration of heterogenous metaheuristic agents. https://doi.org/10.1109/ICDIM.2010.5664656

Collaboration of metaheuristic agents remains as a problem, which attracts challenges to overcome in order to manage a better collaboration in problem solving methodologies. Swarm intelligences techniques have been tried as collaborating methods with... Read More about Collaboration of heterogenous metaheuristic agents.

Swarms of metaheuristic agents: A model for collective intelligence (2010)
Conference Proceeding
Aydin, M. E., Wu, J., & Zhang, L. (2010). Swarms of metaheuristic agents: A model for collective intelligence. In 2010 International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (296-301). https://doi.org/10.1109/3PGCIC.2010.49

Swarm intelligence algorithms are created to build collective intelligence based on inherent properties of populations. However, this sort of problem solving approaches use collective evolution of solutions, which make up the population relied on. Th... Read More about Swarms of metaheuristic agents: A model for collective intelligence.

Coordinating metaheuristic agents with swarm intelligence (2010)
Journal Article
Aydin, M. E. (2012). Coordinating metaheuristic agents with swarm intelligence. Journal of Intelligent Manufacturing, 23(4), 991-999. https://doi.org/10.1007/s10845-010-0435-y

Coordination of multi agent systems remains as a problem since there is no prominent method suggests any universal solution. Metaheuristic agents are specific implementations of multi-agent systems, which imposes working together to solve optimisatio... Read More about Coordinating metaheuristic agents with swarm intelligence.

A new orthogonal array based crossover, with analysis of gene interactions, for evolutionary algorithms and its application to car door design (2010)
Journal Article
Kwong, C. K., Chan, K. Y., Jiang, H., Aydin, M. E., & Fogarty, T. C. (2010). A new orthogonal array based crossover, with analysis of gene interactions, for evolutionary algorithms and its application to car door design. Expert Systems with Applications, 37(5), 3853-3862. https://doi.org/10.1016/j.eswa.2009.11.033

Recent research shows that orthogonal array based crossovers outperform standard and existing crossovers in evolutionary algorithms in solving parametrical problems with high dimensions and multi-optima. However, those crossovers employed so far, ign... Read More about A new orthogonal array based crossover, with analysis of gene interactions, for evolutionary algorithms and its application to car door design.