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With the proliferating development of heuristic methods, it has become challenging to choose the most suitable ones for an application at hand. This paper evaluates the performance of these algorithms available in Matlab, as it is problem dependent and parameter sensitive. Further, the paper attempts to address the challenge that there exists no satisfied benchmarks to evaluation all the algorithms...
The particle filter (PF) offers significant advantages over other nonlinear filters for non-Gaussian systems. However, it suffers from particle degeneracy and impoverishment, which can lead to deteriorated estimation performance. Through analyzing the filtering and Lamarckian evolution processes in this paper, we develop a Lamarckian PF (LPF), based on the assertion that specific characteristics of...
Following analyzing existing challenges in addressing the balance between exploration and exploitation encountered by evolutionary algorithms, this paper develops a Genetic Algorithm with speciation (GASP). It first incorporates a novel encoding scheme and recombination method for a balanced genetic divergence when locating global optima in complex applications, such as structural and dynamic design...
Cloud environments consist of a collection of tasks and heterogeneous resources, the problem of mapping tasks to resources is a major issue. In this paper, we proposed an Improved Adaptive heuristic algorithm (IAHA). At first, the IAHA algorithm makes tasks prioritization in complex graph considering their impact on each other, based on graph topology. Through this technique, completion time of application...
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