Solving complex optimization problems is central to many modern technologies, from logistics and financial modeling to chip ...

In recent years, the frequency of weather-related natural disasters—cyclones, torrential rains, floods—has increased as a consequence of global warming. These disasters cause billions of dollars in ...

Black-box optimization, particularly Bayesian optimization, is a practical approach for weather-intervention design, achieving meaningful rainfall ...

Learn more About two weeks ago, Advanced Micro Devices announced the acquisition of MEXT, a start-up that has built ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Company”), a technology service provider, has announced a groundbreaking achievement of great theoretical and engineering significance: its ...

Arbor separates strategy from execution using isolated git worktrees, so engineering teams can finally trace which optimization actually moved the needle.

Abstract: Large-scale optimization problems (LSOPs) have attracted increasing attention in the big data era. Recently, matrix-based evolutionary computation (MEC) has been proposed as a new diagram ...

In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...

Abstract: This paper introduces a new discrete StarFish Optimization Algorithm (D-SFOA) to solve a complex discrete Symmetric Travelling Salesman Problem (STSP). The discrete SFOA algorithm is ...

The difficulties of algorithmic dynamics in highly nonconvex landscapes are central in several research areas, from hard combinatorial optimization to machine learning. However, it is unclear why and ...