Multiobjective Lightning Flash Algorithm Design and Its Convergence Analysis via Martingale Theory

Joint Authors

Xiao, Gaoxi
Duan, Jiandong
Liu, Xinghua
Wang, Jing

Source

Complexity

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-10-09

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Philosophy

Abstract EN

In this paper, a novel multiobjective lightning flash algorithm (MOLFA) is proposed to solve the multiobjective optimization problem.

The charge population state of the lightning flash algorithm is defined, and we prove that the charge population state sequence is a Markov chain.

Since the convergence analysis of MOLFA is to investigate whether a Pareto optimal solution can be reached when the optimal charge population state is obtained, the development of a charge population state is analyzed to achieve the goal of this paper.

Based on the martingale theory, the MOLFA convergence analysis is carried out in terms of the supermartingale convergence theorem, which shows that the MOLFA can reach the global optimum with probability one.

Finally, the effectiveness of the proposed MOLFA is verified by a numerical simulation example.

American Psychological Association (APA)

Duan, Jiandong& Wang, Jing& Liu, Xinghua& Xiao, Gaoxi. 2020. Multiobjective Lightning Flash Algorithm Design and Its Convergence Analysis via Martingale Theory. Complexity،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1144339

Modern Language Association (MLA)

Duan, Jiandong…[et al.]. Multiobjective Lightning Flash Algorithm Design and Its Convergence Analysis via Martingale Theory. Complexity No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1144339

American Medical Association (AMA)

Duan, Jiandong& Wang, Jing& Liu, Xinghua& Xiao, Gaoxi. Multiobjective Lightning Flash Algorithm Design and Its Convergence Analysis via Martingale Theory. Complexity. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1144339

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1144339