Real-world optimization problems often require an external “modeling engine” that computes fitnesses or data that are then input to an objective function. These programs often have much longer ...

New research published in Operations Research shows that health care systems can substantially reduce overtime, idle time, and overall staffing costs by adopting a multilocation, dynamic ...

This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...

A new peer-reviewed study published in the journal Algorithms signals a major shift in how humanitarian logistics can be ...

This study presents a systematic literature review on humanitarian operations, with emphasis on resource optimization and logistics in forced displacement scenarios. Following a rigorous review ...

Chances are, you’ve seen clicks to your website from organic search results decline since about May 2024—when AI Overviews launched. Large language model optimization (LLMO), a set of tactics for ...

A global research team led by scientists from China’s Tianjin Renai College has developed a novel stochastic optimization technique for enhanced dispatching and operational efficiency in PV-powered ...

Under energy structure transformation and multi-energy complementary development, there is an urgent need to explore more efficient, clean and low-carbon integrated energy utilization. The ...

The AI industry stands at an inflection point. While the previous era pursued larger models—GPT-3's 175 billion parameters to PaLM's 540 billion—focus has shifted toward efficiency and economic ...

Abstract: The emergence of connected vehicle (CV) technology has prompted research on leveraging real-time CV data for more effective traffic signal control. However, existing studies tend to i) ...