IEEE

A Two-Stage Quantum Reinforcement Learning Method for Multi-Objective Transmission Switching

Abstract: Multi-objective transmission switching (MO-TS) problems involve the strategic reconfiguration of network topology to simultaneously optimize multiple objectives. As the system scale ...
The New York Times

She Died After Her Pacemaker Battery Failed. Its Maker Knew of Problems for Years.

Boston Scientific announced multiple recalls but has said its battery issues were limited. One internal test in 2025 found batteries with an “extremely high failure rate.” Credit...Illustration by Mel ...
Scientific Research Publishing

Umarusman, N. (2013) Min-Max Goal Programming Approach for Solving Multi-Objective de Novo Programming Problems. International Journal of Operations Re-search, 10, 92-99.

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...
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 ...
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 ...
EurekAlert!

Deep reinforcement learning optimizes distributed manufacturing scheduling

A recent study published in Engineering presents a significant advancement in manufacturing scheduling. Researchers Xueyan Sun, Weiming Shen, Jiaxin Fan, and their colleagues from Huazhong University ...