Marcus Furuholmen

Fornebu Consulting (Norway), University of Oslo

Papers

Total Citations

H-Index

About

Marcus Furuholmen’s research lies at the intersection of evolutionary computation, industrial robotics, and adaptive systems, with a focus on solving complex, real-world engineering challenges. His most notable contribution is the development of **Indirect Online Evolution (IDOE)** , a conceptual framework that enables robotic systems to continuously adapt to changing environments without human intervention. In this framework, a “model specie” uses Gene Expression Programming (GEP) to autonomously infer models of hidden physical systems, while a “parameter specie” optimizes system parameters in real time. This work, presented in two 2008 papers, laid the groundwork for self-adaptive industrial robotics. Furuholmen also made significant strides in optimization with his 2010 comparative study on evolutionary approaches to the **three-dimensional multi-pipe routing problem**, a notoriously difficult design task in manufacturing and aerospace. His direct encoding comparisons provided practical insights for engineers tackling spatial layout optimization. While his citation counts (14 for his top paper) reflect a niche but dedicated audience, his IDOE framework represents a forward-thinking vision for autonomous adaptation in robotics—a concept increasingly relevant in modern Industry 4.0 applications.