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Dynamic optimization is one of the important research area in the intelligence computation field. For a decade, various dynamic benchmark test functions have been put forward. Generally speaking, though these functions help to improve a lot on the dynamic algorithms design, the fact that the whole landscape might affects the algorithm's performance rather than that of the way it changes is ignored...
A comparative study of θ-PSO and its improved model with partial particles randomization strategy on their abilities of tracking extrema in dynamic environments was carried out in our earlier work. And the results shown that θ-PSO has better performance in dynamic optimization than standard PSO. In this paper, an improved θ-PSO with memory recall and varying scale randomization strategy (θ-PSO-MR)...
Along with the rapid growth of the number of the available Web services over the Internet, the quality of services (QoS) becomes an imperative concern for service consumers and providers. How to differentiate their quality based on Qos criteria at Web service level is a challenging issue. Considering that evolutionary algorithm has powerful ability of searching information, a new Web service composition...
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