Frontiers

CLMOAS: collaborative large-scale multi-objective optimization algorithms with adaptive strategies

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 ...
Search Engine Land

LLM optimization in 2026: Tracking, visibility, and what’s next for AI discovery

Marketing, technology, and business leaders today are asking an important question: how do you optimize for large language models (LLMs) like ChatGPT, Gemini, and Claude? LLM optimization is taking ...
IEEE

Multi-Party Multi-Objective Optimization for Discrete Problems: A Case Study on Multi-Stakeholder Recommendation

Abstract: Multi-party multi-objective optimization, which aims to find a solution set that satisfies multiple decision makers (DMs) as much as possible, has attracted the attention of researchers ...
Frontiers

Robust multi-objective optimization framework for performance-based seismic design of steel frame with energy dissipation system

1 Guangzhou Institute of Building Science Group Co., Ltd., Guangzhou, Guangdong, China 2 Glenn Department of Civil Engineering, Clemson University, Clemson, SC, United States Modern seismic codes ...
IEEE

Multi-Objective Optimization for Multimodal Multi-Objective Multi-Point Shortest Path Problem Considering Unforeseeable Road Eventualities

Abstract: Multi-objective multi-point shortest path planning problems are commonly encountered in real-world applications. Numerous path planning algorithms have been proposed to accommodate different ...
EurekAlert!

A new perspective on designing urban low-altitude logistics networks subhead: Balancing cost, safety, and noise through co-evolutionary multi-objective optimization

The urban low-altitude logistics network adopts a hub-and-spoke, multi-layered structure. Its nodes are waypoints mapped to corresponding altitude layers based on spoke nodes (delivery spots) and hub ...