Abstract
Most of existing swarm intelligence (SI) algorithms is modeling based on natural phenomena. Firstly, different from the previous practices, this paper constructs a mathematical model based on the traditional optimization algorithms. To simplify this model, a new algorithm Linear Transformation and Elitist Selection algorithm (LTES) is proposed. Experiment shows that the algorithm has origin illusion phenomenon. Then, this paper observes origin illusion phenomenon for the population-based optimization algorithm, and experiments shows that crossover operator is an effective way for LTES’ origin illusion problem. Finally, another algorithm Contraction and Guidance Algorithm (CGA) is proposed to prove that elitist selection is not necessary. The experimental results show that both algorithms are effective.
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This research is supported by National Natural Science Foundation of China (61375066, 71772060).
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Li, R., Xu, G., Zhao, X., Gong, D. (2018). Origin Illusion, Elitist Selection and Contraction Guidance. In: Qiao, J., et al. Bio-inspired Computing: Theories and Applications. BIC-TA 2018. Communications in Computer and Information Science, vol 951. Springer, Singapore. https://doi.org/10.1007/978-981-13-2826-8_35
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DOI: https://doi.org/10.1007/978-981-13-2826-8_35
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