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Benchmarking based search framework

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Abstract

Most of the issues in science, engineering, and management can be turned into optimization problems by modeling. However, for most of which, the operations research methods based on rigid mathematical logic can do nothing, intelligent methods are helpful. Traditionally, the so-called intelligent methods, whose “intelligence” is mainly dependent on the probability rules of their operators. Thus there are always some probability equations or mathematical formulations that need to be updated. This paper proposed a new framework for intelligent optimization/search, which is based on artful organizing tactics rather than “intelligent” probability rules. Thus it needs no probability equations. In addition, it is helpful to balance the exploration and the exploitation, keep the population diversity and avoid useless and ineffective repetitious operations. The mentioned above had been proved by theoretical analyses and simulation experiments. Of course, any method has its disadvantages, the defects and the possible improvement measures of this framework were summarized in the conclusion part.

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Acknowledgements

This research is supported by the research fund [grant number 16JDGH048] from “Collaborative innovation center for Transformation and Upgrading of Micro, Small and Medium Enterprises, Zhejiang University of Technology”, “Zhejiang Provincial New Key Professional Think Tank - China Institute for SMEs, Zhejiang University of Technology”. The mentors of my student times provided me with good edification. The colleagues of my department have provided me with a favorable environment, and I would like to express my gratitude.

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    A. S. Xie

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Xie, A.S. Benchmarking based search framework. Cluster Comput 22, 929–951 (2019). https://doi.org/10.1007/s10586-018-2881-9

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