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DSSO-Directional Shrinking Search Optimization

机译:DSSO方向缩小搜索优化

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摘要

Researchers are continuously trying to develop new heuristic search algorithms in the field of optimization. In this paper, a novel optimization technique has been proposed that tries to maximize the effectiveness of exploration and exploitation by the algorithms in the search of global optimum point. In this proposed algorithm, the points in the search regions are directing towards the global optimum point in the same time the search region is also starts reducing exponentially. A stochastic process has been added in the end of the algorithm to provide better exploitation of the search region. The performance of the algorithm has been compared with some well known optimization techniques and the derived empirical results on solving standard benchmark functions clearly signifies the high performance of the proposed algorithm.
机译:研究人员不断尝试在优化领域开发新的启发式搜索算法。本文提出了一种新颖的优化技术,以最大限度地试图通过算法在全球最佳点寻找算法中最大限度地提高探索和利用的有效性。在该提出的算法中,搜索区域中的点在搜索区域的同时引导到全局最佳点,同时也开始指数地减少。在算法结束时添加了随机过程,以提供更好的搜索区域利用。已经将算法的性能与一些众所周知的优化技术进行了比较,并且求解标准基准函数的导出的经验结果明确表示所提出的算法的高性能。

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