Elitism-based immigrants for ant colony optimization in dynamic environments: Adapting the replacement rate
The integration of immigrants schemes with ant colony optimization (ACO) algorithms showed promising results on different dynamic optimization problems (DOPs). The principle of integrating immigrants schemes within ACO is to introduce newly generated ants that will replace other ants in the current population. One of the most advanced immigrants schemes is the elitism-based immigrants scheme, where the best ant from the previous environment is used as the base to generate immigrants. So far, the replacement rate used for elitism-based immigrants in ACO remained fixed during the execution of the algorithm. In this paper the impact of the replacement rate on the performance of ACO algorithms with elitism-based immigrants is examined. In addition, an adaptive replacement rate is proposed and compared with fixed and optimized replacement rates based on a series of DOPs. The experiments show that the adaptive scheme provides an automatic way to set a good value, although not the optimal one, for the replacement rate within ACO with elitism-based immigrants for DOPs.
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Citation : Mavrovouniotis, M. and Yang, S. (2014) Elitism-based immigrants for ant colony optimization in dynamic environments: Adapting the replacement rate. Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC), Beijing, China, July 2014, pp. 1752-1759.
ISBN : 9781479914883
Research Institute : Institute of Artificial Intelligence (IAI)
Peer Reviewed : Yes