Optimal Vessel Planning in Natural Inland Waterways

Juan Moreno Nadales received his BSc in Electronic Engineering from the University of Cordoba in 2017. He moved to the University of Seville where he received his MSc in Control and System Engineering in 2018, specializing in model predictive control, and his MSc in Microelectronic Design in 2019, specializing in the implementation of bio-inspired algorithms on configurable embedded platforms. He received the PhD in Control and Systems Engineering from the University of Seville in 2024, specializing in the application of robust model predictive control techniques to safe navigation management. In 2022 he carried out a research stay at Seoul National University, Republic of Korea, in collaboration with the Optimization and Control Research Lab. His main research line is the application of new predictive control strategies and optimization techniques to different fields such as logistics, power electronic systems, or intelligent air conditioning systems. From 2024, he is a post-doctoral researcher at the Earth-Life Science Institute (ELSI) of Tokyo Institute of Technology, Japan, where he specializing in artificial life and the integration of integration of living organisms with computational entities in shared ecosystems.

David Muñoz de la Peña was born in Badajoz, Spain, in 1978. He received the Laurea degree in telecommunication engineering in 2001, and the Ph.D. degree in automation, robotic, and telecommunication in 2005, both from the University of Seville, Spain. He spent the academic year 2003-2004 at the Systems Control Group at the Department of Information Engineering of the University of Siena. In 2006-2007, he held a post-doctoral position at the Chemical and Biomolecular Engineering Department at the University of California Los Angeles. Since 2007, he is with the Department of Automation and Systems Engineering of the University of Seville, becoming a full professor in 2017. His theoretical research interests include model predictive control, distributed systems, process control, multiparametric optimization, and machine learning. His research work has resulted in a large number of articles in leading scientific journals and conferences.

Daniel Limon received the M.Eng. and Ph.D. degrees in electrical engineering from the University of Seville, Seville, Spain, in 1996 and 2002, respectively. From 1999 to 2007, he was an Assistant Professor with the Departamento de Ingeniería de Sistemas y Automática, University of Seville, from 2007 to 2017 Associate Professor and since 2017, Full Professor in the same Department. He has been visiting researcher at the University of Cambridge and the Mitsubishi Electric Research Labs in 2016 and 2018 respectively. Dr. Limon has been a Keynote Speaker at the International Workshop on Assessment and Future Directions of Nonlinear Model Predictive Control in 2008 and Semiplenary Lecturer at the IFAC Conference on Nonlinear Model Predictive Control in 2012. He has been the Chair of the fifth IFAC Conference on Nonlinear Model Predictive Control (2015). His current research interests include model predictive control, stability and robustness analysis, tracking control, optimal operation and data-based control with application to buildings and water distribution networks, spacecraft rendevouz strategies and navigation planning.

Teodoro Alamo received the M.Eng. degree in telecommunications engineering from the Polytechnic University of Madrid in 1993, and the PhD degree in telecommunications engineering from the University of Seville in 1998. He has been a Full Professor of the Department of Automation and Systems Engineering in the University of Seville since 2010. He was with the Ecole Nationale Superieure des Télécommunications (Télécom Paris), Paris, France, from September 1991 to May 1993. Part of his PhD work was done at RWTH Aachen, Germany, from June to September 1995. He has co-founded the spin-off company Optimal Performance (University of Seville). He is the author or co-author of more than 200 publications, including books, book chapters, journal articles, and conference proceedings. His current research interests include decision-making, model predictive control, data-driven methods, randomized algorithms, and optimization strategies.

胡安·莫雷諾·納達萊斯（Juan Moreno Nadales）於2017年獲得科爾多瓦大學的電子工程學士學位。隨後，他轉學至塞維利亞大學，於2018年獲得控制與系統工程碩士學位，專攻模型預測控制，並於2019年獲得微電子設計碩士學位，專注於在可配置嵌入式平台上實現生物啟發算法。他於2024年獲得塞維利亞大學的控制與系統工程博士學位，專注於穩健模型預測控制技術在安全導航管理中的應用。2022年，他在韓國首爾國立大學進行了研究訪問，與優化與控制研究實驗室合作。他的主要研究方向是將新的預測控制策略和優化技術應用於物流、電力電子系統或智能空調系統等不同領域。自2024年起，他成為日本東京科技大學地球生命科學研究所（ELSI）的博士後研究員，專注於人工生命及生物體與計算實體在共享生態系統中的整合。

大衛·穆尼奧斯·德拉佩尼亞（David Muñoz de la Peña）於1978年出生於西班牙巴達霍斯。他於2001年獲得電信工程學位，並於2005年獲得自動化、機器人和電信的博士學位，均來自塞維利亞大學。他在2003-2004學年於西耶那大學信息工程系的系統控制組進行學術交流。2006-2007年，他在加州大學洛杉磯分校的化學與生物分子工程系擔任博士後職位。自2007年以來，他在塞維利亞大學的自動化與系統工程系任教，並於2017年成為正教授。他的理論研究興趣包括模型預測控制、分佈式系統、過程控制、多參數優化和機器學習。他的研究工作在領先的科學期刊和會議上發表了大量文章。

丹尼爾·利蒙（Daniel Limon）於1996年和2002年分別在塞維利亞大學獲得電氣工程碩士和博士學位。1999年至2007年，他在塞維利亞大學的系統與自動化工程系擔任助理教授，2007年至2017年擔任副教授，自2017年起成為該系的正教授。他曾於2016年和2018年分別在劍橋大學和三菱電機研究所擔任訪問研究員。利蒙博士於2008年在非線性模型預測控制的國際研討會上擔任主題演講者，並於2012年在IFAC非線性模型預測控制會議上擔任半主題演講者。他曾擔任第五屆IFAC非線性模型預測控制會議的主席（2015年）。他目前的研究興趣包括模型預測控制、穩定性和魯棒性分析、跟蹤控制、最佳操作及基於數據的控制，應用於建築物和水分配網絡、航天器會合策略和導航規劃。

特奧多羅·阿拉莫（Teodoro Alamo）於1993年獲得馬德里理工大學的電信工程碩士學位，並於1998年獲得塞維利亞大學的電信工程博士學位。自2010年以來，他一直是塞維利亞大學自動化與系統工程系的正教授。他曾於1991年9月至1993年5月在法國巴黎的國立電信高等學校（Télécom Paris）工作。他的部分博士研究工作於1995年6月至9月在德國亞琛工業大學進行。他是...