IEEE

AutoOpt: A General Framework for Automatically Designing Metaheuristic Optimization Algorithms With Diverse Structures

Abstract: Metaheuristics are widely recognized gradient-free solvers to hard problems that do not meet the rigorous mathematical assumptions of conventional solvers. The automated design of ...
Communications of the ACM

The LLVM Compiler Infrastructure

LLVM powers the core development tools, operating systems, and most applications at Apple Computer, where it long ago ...
Frontiers

Multi-objective Forest Management under Global Change: Forest Ecosystem Response Mechanisms and Resource Utilization

Against the backdrop of global change—characterized by climate warming, shifting precipitation patterns, and intensified anthropogenic disturbances—the ...

Black-box optimization weather intervention method supports future disaster mitigation

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 ...

61% of CMOs Say Local Marketing Is Too Complex: Here’s the Fix

Learn how multi-location brands fix complex marketing & GBP challenges with an AI layer and a 4-step local optimization ...

Multi-Location SEO: How To Win Google & AI Search Visibility At Scale

Multi-location brands must adapt to fragmented search visibility across Google, Maps, AI assistants, and social platforms.
IEEE

Automated Configuration of Evolutionary Algorithms via Deep Reinforcement Learning for Constrained Multiobjective Optimization

Abstract: Learning to optimize and automated algorithm design are attracting increasing attention, but it is still in its infancy in constrained multiobjective optimization evolutionary algorithms ...