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A construction method for large scale global optimization problem
Author(s): Hao Chen; Yuan Chen; Chunlei Xu
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Paper Abstract

Large scale global optimization problems are closely related to real-life; however, the existing test function sets for large scale optimization problems can not truly reflect the complexity of the actual optimization problem. This paper presents a method for constructing test function sets, it can generate complex test function with different correlation, different deception and different difficulty of solving by adjusting the key parameters such as encoding length, number of groups, equipartition, continuity and the upper and lower limits of the dimensions within the group, it can be controlled by correlation, deception and continuity among dimensions. Using the existing metric correlation index verified the validity of the new construction test functions, and it can effectively simulate the incompletely separable optimization problem with different complexity.

Paper Details

Date Published: 23 January 2019
PDF: 7 pages
Proc. SPIE 10835, Global Intelligence Industry Conference (GIIC 2018), 1083505 (23 January 2019); doi: 10.1117/12.2505031
Show Author Affiliations
Hao Chen, Nanchang Hangkong Univ. (China)
Yuan Chen, Nanchang Hangkong Univ. (China)
Chunlei Xu, Nanchang Hangkong Univ. (China)


Published in SPIE Proceedings Vol. 10835:
Global Intelligence Industry Conference (GIIC 2018)
Yueguang Lv, Editor(s)

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