Self Adaptive Cluster Based and Weed Inspired Differential Evolution Algorithm For Real World Optimization

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Provided by: Institute of Electrical & Electronic Engineers
Topic: Big Data
Format: PDF
In this paper, the authors propose a Self Adaptive Cluster based and Weed Inspired Differential Evolution algorithm (SACWIDE), the total population is divided into several clusters based on the positions of the individuals and the cluster number is dynamically changed by the suitable learning strategy during evolution. Here, they incorporate a modified version of the Invasive Weed Optimization (IWO) algorithm as a local search technique. The algorithm strategically determines whether a particular cluster will perform Differential Evolution (DE) or the IWO algorithm.
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