The Continuous Differential Ant-Stigmergy Algorithm applied on real-parameter single objective optimization problems
作者： Peter Korosec , Jurij Silc
关键词: Derivative-free optimization 、 Algorithm 、 Meta-optimization 、 Multi-swarm optimization 、 Optimization problem 、 Metaheuristic 、 Mathematical optimization 、 Mathematics 、 Continuous optimization 、 Test functions for optimization 、 Discrete optimization
摘要: Continuous ant-colony optimization is an emerging field in numerical optimization, which tries to cope with the challenges arising modern real-world engineering and scientific domains. One of them large-scale continuous problem that becomes especially important for development recent fields like bio-computing, data mining production planing. Ant-colony (ACO) known its efficiency solving combinatorial problems. However, application real-parameter optimizations appears more challenging, since pheromone-laying method not straightforward. In year, there have been developed a several adaptations ACO algorithm optimization. Among Differential Ant-Stigmergy Algorithm (CDASA) arises as promising global this paper we address systematic performance evaluation CDASA on predefined test suite experimental procedure provided Competition Real-Parameter Single Objective Optimization at CEC-2013.
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