Hybrid opposite-based learning marine predator algorithm

Junqi Geng; Xinghua Liu

doi:10.1117/12.2678964

25 May 2023 Hybrid opposite-based learning marine predator algorithm

Junqi Geng, Xinghua Liu

Proceedings Volume 12712, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023); 127121T (2023) https://doi.org/10.1117/12.2678964
Event: International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023), 2023, Huzhou, China

Abstract

The marine predators algorithm (MPA) is a swarm-based metaheuristic algorithm which present good performance, but suffers from insufficient population diversity. To enhance the population diversity and prevent the algorithm searching for a partial optimal solution, in this paper, we suggest a hybrid opposite-based learning marine predator algorithm. In HOLMPA, the performance is improved by introducing two different opposite learning strategies. The effectiveness of HOLMPA is verified by applying a group of test functions.

Citation Download Citation

Junqi Geng and Xinghua Liu "Hybrid opposite-based learning marine predator algorithm", Proc. SPIE 12712, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023), 127121T (25 May 2023); https://doi.org/10.1117/12.2678964

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available