A Population-Based Optimization Method Using Newton Fractal

Joint Authors

Lee, Chang Hyeong
Kim, Pilwon

Source

Complexity

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-9, 9 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-02-03

Country of Publication

Egypt

No. of Pages

9

Main Subjects

Philosophy

Abstract EN

We propose a deterministic population-based method for a global optimization, a Newton particle optimizer (NPO).

The algorithm uses the Newton method with a guiding function and drives particles toward the current best positions.

The particles’ movements are influenced by the fractal nature of the Newton method and are greatly diversified in the approach to the temporal best optimums.

As a result, NPO generates a wide variety of searching paths, achieving a balance between exploration and exploitation.

NPO differs from other metaheuristic methods in that it combines an exact mathematical operation with heuristics and is therefore open to more rigorous analysis.

The local and global search of the method can be separately handled as properties of an associated multidimensional mapping.

American Psychological Association (APA)

Lee, Chang Hyeong& Kim, Pilwon. 2019. A Population-Based Optimization Method Using Newton Fractal. Complexity،Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1132099

Modern Language Association (MLA)

Lee, Chang Hyeong& Kim, Pilwon. A Population-Based Optimization Method Using Newton Fractal. Complexity No. 2019 (2019), pp.1-9.
https://search.emarefa.net/detail/BIM-1132099

American Medical Association (AMA)

Lee, Chang Hyeong& Kim, Pilwon. A Population-Based Optimization Method Using Newton Fractal. Complexity. 2019. Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1132099

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1132099