Deep Learning-Based Step Size Determination for Hill Climbing Metaheuristics
Machine Learning-assisted metaheuristics is a new and promising research topic, combining the advantages of both method families. Metaheuristics are widely used general problem solvers that can be fine-tuned by prior knowledge about the search space; however, this adaptation can be a very time-consu...
Saved in:
| Main Authors: | Sándor Szénási, Gábor Légrádi, Gábor Kovács |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Algorithms |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4893/18/5/298 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Variable Step-size Hill-Climbing Search (VS-HCS) MPPT Algorithm for Hydrokinetic Energy Harnessing
by: WAN ISMAIL IBRAHIM, et al.
Published: (2025-06-01) -
Hybrid Population-Based Hill Climbing Algorithm for Generating Highly Nonlinear S-boxes
by: Oleksandr Kuznetsov, et al.
Published: (2024-12-01) -
Stock portfolio optimization using hill climbing and simple human learning optimization algorithms as a decision support system
by: Suyash S. Satpute, et al.
Published: (2025-06-01) -
HILL CLIMBING ALGORITHM ON BAYESIAN NETWORK TO DETERMINE PROBABILITY VALUE OF SYMPTOMS AND EYE DISEASE
by: Ria Puan Adhitama, et al.
Published: (2022-12-01) -
PERBANDINGAN ALGORITMA HILL CLIMBING DAN ALGORITMA ANT COLONY DALAM PENENTUAN RUTE OPTIMUM
by: Venn Y. I. Ilwaru, et al.
Published: (2017-12-01)