Huisheng Liu Examines Multi-Cloud MLOps as a Path to More Reliable Commercial AI Services

A multi-cloud MLOps framework improves AI service reliability through automated deployment, canary releases, and ...
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 ...
AOL

GOP Sen. Tillis says objectives of Iran war unclear: 'It's a real problem'

ABC News - PHOTO: Sen. Thom Tillis, R-N.C., appears on ABC News' "This Week" on March 22, 2026. As the war with Iran enters its fourth week, Republican Sen. Thom Tillis said the Trump administration ...
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 ...
GitHub

Knowledge Gradient for Multi-Objective Bayesian Optimization with Decoupled Evaluations

This repository contains the code to run the experiments in the paper (Buckingham et al., 2025): Buckingham, J. M., Rojas Gonzalez, S., & Branke, J. (2025). Knowledge Gradient for Multi-Objective ...
IEEE

Multi-Objective Optimization for Traveling Salesman Problem: A Deep Reinforcement Learning Algorithm via Transfer Learning

Impact Statement: The multi-objective traveling salesman problem (MOTSP), one of the typical combinatorial optimization problems, can be used to model a broad range of real applications.
Microsoft

Ranking with Multiple Objectives

In search and advertisement ranking, it is often required to simultaneously maximize multiple objectives. For example, the objectives can correspond to multiple intents of a search query, or in the ...