Lluis Miquel | Operations Research | Mathematical Modeling Breakthrough Award

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Prof. Dr. Lluis Miquel | Operations Research | Mathematical Modeling Breakthrough Award

Departamento Matemática at Pla-Aragones Universidad de Lleida, Spain

Dr. Luis Miguel Plà-Aragonès 🇪🇸 is a renowned expert in Operations Research 🔍 and Decision Analysis 🧠, with a focus on applications in agriculture 🌾, economics 💹, and health systems 🏥. As a professor at the University of Lleida, Spain, he has made significant contributions through multi-criteria decision-making, optimization modeling, and policy analysis. His interdisciplinary approach bridges the gap between theory and real-world impact, particularly in areas like agricultural planning, resource allocation, and cost-effectiveness analysis. 📊 With numerous publications 📚 and collaborations across Europe and Latin America 🌍, Dr. Plà-Aragonès is recognized for advancing the role of decision science in solving complex societal challenges. He is a dedicated mentor 👨‍🏫, respected academic, and a driving force behind the integration of quantitative models into sustainable decision-making practices. ♻️

Professional Profile 

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🎓 Education

Dr. Luis Miguel Plà-Aragonès holds a Ph.D. in Agricultural Engineering 🧑‍🔬 from the University of Lleida, Spain 🇪🇸, where he also earned his undergraduate and master’s degrees. His academic journey has been deeply rooted in applying mathematical and decision-analytic tools 📐 to complex agricultural systems 🌾. With a strong foundation in statistics, optimization, and operations research, he further enriched his expertise through postdoctoral training and international research exchanges across Europe 🌍. His educational background blends technical rigor with practical insight, laying the groundwork for his interdisciplinary research. His early academic excellence and commitment to innovation have made him a respected scholar in quantitative decision-making 🧠, particularly within the agricultural and environmental sectors. 📊 His educational path has continuously evolved toward bridging scientific research and real-world problem solving. 🧑‍🏫

💼 Professional Experience

Dr. Plà-Aragonès serves as a Professor of Operations Research and Decision Analysis at the University of Lleida 🏛️, with more than two decades of academic experience 👨‍🏫. He has held leadership roles in multiple international research networks, including coordinating the EURO Working Group on Operational Research in Agriculture and Forest Management 🌳. His career spans collaborative projects with both academic and industry stakeholders, particularly in the pig and dairy farming sectors 🐖🐄. As a principal investigator, he has led EU and Latin American research consortia in modeling and AI-driven agricultural innovation 🤖. He also mentors Ph.D. students and has developed decision-support systems used in real-world agribusiness. His dynamic professional profile showcases a balance of teaching, research, consultancy, and technological transfer across interdisciplinary domains. 🌍

🔬 Research Interests

Dr. Plà-Aragonès’s research revolves around mathematical modeling, multi-criteria decision-making, and operations research applied to agriculture, healthcare, and resource management 🌾🏥📊. He is especially known for his work in livestock logistics, sow replacement optimization, and agri-food supply chain modeling using Markov Decision Processes, stochastic optimization, and AI-enhanced systems 🤖. His interests also extend to cost-effectiveness analysis in healthcare, bridging economic modeling with decision science 💊. He is a key advocate for integrating AI, cloud computing ☁️, and IoT into agricultural modeling, ensuring smarter and more sustainable farm management. Through international collaborations 🌍 and cross-sector applications, his research continually addresses real-world challenges in food systems, environmental sustainability ♻️, and public health policy using rigorous quantitative methods. 📈

🏅 Awards and Honors

Dr. Luis Miguel Plà-Aragonès has been honored for his outstanding contributions to operations research and agricultural modeling 🌍. He is a recipient of various research leadership recognitions, including the prestigious coordination role in the CYTED BigDSSAgro Network and awards from international agricultural and engineering bodies 🧪. His work has earned accolades for bridging research and practice in farming systems, and he has been frequently invited as a keynote speaker 🎤 at global conferences in AI for agriculture and decision support systems. Under his leadership, several European Union and international collaborative projects have won funding and academic praise 💼💡. His active role in mentoring, publishing, and innovating across disciplines has made him a respected and decorated figure in decision science and sustainable development. 🥇

🧰 Research Skills

Dr. Plà-Aragonès possesses advanced skills in mathematical modeling, optimization, stochastic processes, and simulation modeling 🔢. He is adept in applying Markov Decision Processes, Multi-Criteria Decision Analysis (MCDA), and AI algorithms to develop decision-support tools for agriculture and health sectors 🌱🏥. His programming capabilities span R, Python, and MATLAB, while his modeling expertise extends to GAMS, LINGO, and AnyLogic 💻. He’s proficient in integrating data analytics, machine learning, and cloud-based architectures for developing scalable, digital decision systems ☁️🤖. Dr. Plà’s multidisciplinary skills allow him to lead cross-border research, publish in top-tier journals 📚, and translate theory into practical tools for industry. His ability to synthesize quantitative methods into actionable solutions defines his technical excellence. ⚙️

Publications Top Note 📝

  • Title: Operational research models applied to the fresh fruit supply chain
    Authors: WE Soto-Silva, E Nadal-Roig, MC González-Araya, LM Plà-Aragonès
    Year: 2016
    Citations: 337
    Source: European Journal of Operational Research, 251(2), 345-355

  • Title: Sugar cane transportation in Cuba, a case study
    Authors: EL Milan, SM Fernandez, LMP Aragones
    Year: 2006
    Citations: 132
    Source: European Journal of Operational Research, 174(1), 374-386

  • Title: Optimizing fresh food logistics for processing: Application for a large Chilean apple supply chain
    Authors: WE Soto-Silva, MC González-Araya, MA Oliva-Fernández, et al.
    Year: 2017
    Citations: 123
    Source: Computers and Electronics in Agriculture, 136, 42-57

  • Title: A perspective on operational research prospects for agriculture
    Authors: LM Plà, DL Sandars, AJ Higgins
    Year: 2014
    Citations: 101
    Source: Journal of the Operational Research Society, 65(7), 1078–1089

  • Title: Review of mathematical models for sow herd management
    Authors: LM Plà
    Year: 2007
    Citations: 66
    Source: Livestock Science, 106(2–3), 107–119

  • Title: New opportunities in operations research to improve pork supply chain efficiency
    Authors: SV Rodríguez, LM Plà, J Faulin
    Year: 2014
    Citations: 63
    Source: Annals of Operations Research, 219, 5–23

  • Title: A Markov decision sow model representing the productive lifespan of herd sows
    Authors: LM Plà, C Pomar, J Pomar
    Year: 2003
    Citations: 53
    Source: Agricultural Systems, 76(1), 253–272

  • Title: Environmental assessment of a pork-production system in North-East of Spain focusing on life-cycle swine nutrition
    Authors: C Lamnatou, X Ezcurra-Ciaurriz, D Chemisana, LM Plà-Aragonès
    Year: 2016
    Citations: 52
    Source: Journal of Cleaner Production, 137, 105–115

  • Title: Optimal transport planning for the supply to a fruit logistic centre
    Authors: E Nadal-Roig, LM Plà-Aragonès
    Year: 2015
    Citations: 51
    Source: Handbook of Operations Research in Agriculture and the Agri-Food Industry

  • Title: Modeling tactical planning decisions through a linear optimization model in sow farms
    Authors: SV Rodríguez-Sánchez, LM Plà-Aragonès, VM Albornoz
    Year: 2012
    Citations: 50
    Source: Livestock Science, 143(2–3), 162–171

  • Title: Production planning of supply chains in the pig industry
    Authors: E Nadal-Roig, LM Plà-Aragonès, A Alonso-Ayuso
    Year: 2019
    Citations: 42
    Source: Computers and Electronics in Agriculture, 161, 72–78

  • Title: A two-stage stochastic programming model for scheduling replacements in sow farms
    Authors: SV Rodríguez, VM Albornoz, LM Plà
    Year: 2009
    Citations: 42
    Source: TOP, 17, 171–189

  • Title: Handbook of operations research in agriculture and the agri-food industry
    Author: LM Plà-Aragonès
    Year: 2015
    Citations: 41
    Source: Springer New York

  • Title: Selection of slaughterhouse to deliver fattened pigs depending on growth curves
    Authors: Y Bao, P Llagostera, D Babot, LM Plà-Aragonès
    Year: 2025
    Source: Agricultural Systems, 229, 104406

  • Title: Mathematical methods applied to the problem of dairy cow replacements: a scoping review
    Authors: O Palma, LM Plà-Aragonès, A Mac Cawley, VM Albornoz
    Year: 2025
    Source: Animals, 15(7), 970

  • Title: A genetic algorithm for site-specific management zone delineation
    Authors: F Huguet, LM Plà-Aragonès, VM Albornoz, M Pohl
    Year: 2025
    Source: Mathematics, 13(7), 1064

  • Title: A deep learning approach for image analysis and reading body weight from digital scales in pigs farms
    Authors: NA Reyes-Reyes, MC Doja, P Llagostera-Blasco, LM Plà-Aragonès, et al.
    Year: 2025
    Source: IEEE Access

  • Title: Mathematical Methods Applied to the Problem of Dairy Cow Replacements: A Scoping Review
    Authors: O Palma, LM Plà-Aragonès, A Mac Cawley, VM Albornoz
    Year: 2025
    Source: System, 26, 11

🧭 Conclusion

Dr. Luis Miguel Plà-Aragonès exemplifies the fusion of theoretical innovation and practical impact in mathematical modeling 🌍. With a foundation built on rigorous education 🎓 and two decades of professional excellence 💼, he has become a global leader in using operations research to solve real-world problems in agriculture, environment, and health 🌾💊♻️. His interdisciplinary collaborations, influential publications, and award-winning leadership reflect a visionary commitment to data-driven decision-making 📈. By integrating AI, cloud systems, and analytics into sustainable frameworks, Dr. Plà is shaping the future of intelligent agriculture and policy modeling 🤖. His dedication to mentorship, international outreach, and technological innovation makes him not only a researcher of high distinction but also a catalyst for global scientific progress. 🏆

Shijie Zhao | Applied Mathematics | Best Researcher Award

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Assoc. Prof. Dr. Shijie Zhao | Applied Mathematics | Best Researcher Award

Associate Professor at Liaoning Technical University, China

Assoc. Prof. Dr. Shijie Zhao is a distinguished researcher and academic at the Institute of Intelligence Science and Optimization, Liaoning Technical University, China. With a Ph.D. in Optimization and Management Decisions, his expertise lies in metaheuristic optimization, multi-objective optimization, and underwater navigation and positioning. He has made significant contributions through innovative algorithm designs and novel mathematical models, particularly in high-dimensional feature selection and robust navigation techniques. Dr. Zhao has published 9 SCI-indexed journal articles and participated in over 10 nationally and provincially funded research projects. He serves as a reviewer for leading journals including those by Elsevier, Springer, and IEEE, and holds memberships in 13 professional bodies. With strong programming skills, rigorous analytical thinking, and a commitment to scientific innovation, Dr. Zhao has also earned four research awards. His work bridges theoretical mathematics and practical applications, making him a valuable contributor to the global research community in intelligent systems and optimization.

Professional Profile 

Scopus Profile
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Education

Assoc. Prof. Dr. Shijie Zhao has a robust academic foundation anchored at Liaoning Technical University, China. He earned his B.S. degree in Science of Information & Computation in 2012, followed by a successive postgraduate and doctoral program in Mathematics and Applied Mathematics from 2012 to 2014. He went on to complete his Ph.D. in Optimization and Management Decisions in 2018. His educational trajectory highlights a deep commitment to the field of mathematical optimization and intelligent systems. Dr. Zhao’s academic excellence is also reflected in his ability to integrate theoretical knowledge with practical problem-solving, laying a strong foundation for his future research. His interdisciplinary approach blends pure mathematics with applied optimization techniques, making him uniquely positioned to contribute to emerging challenges in computational intelligence, machine learning, and navigation systems. His comprehensive training has equipped him with skills in advanced mathematical modeling, algorithm design, and statistical analysis—all crucial for his research trajectory.

Professional Experience

Dr. Shijie Zhao began his professional journey as a faculty member at Liaoning Technical University, where he is now serving as an Associate Professor and Director of the Institute of Intelligence Science and Optimization. Since 2012, he has progressed through a series of academic roles, including a postdoctoral tenure beginning in 2020. He has successfully led and participated in a range of scientific research projects sponsored by institutions such as the China Postdoctoral Science Foundation and the Department of Science & Technology of Liaoning Province. In addition to his teaching responsibilities, he has been actively involved in administrative, academic, and research leadership roles. Dr. Zhao has served as a reviewer for numerous high-impact international journals and conferences and has editorial roles in reputed scientific publications. His contributions to collaborative and interdisciplinary projects underscore his ability to bridge research and real-world applications, enhancing his standing as a key contributor in intelligent systems research.

Research Interest

Assoc. Prof. Dr. Shijie Zhao’s research interests lie at the intersection of intelligent optimization, computational mathematics, and advanced data analytics. He specializes in the development and enhancement of metaheuristic and multi-objective optimization algorithms, addressing both theoretical and application-driven challenges. His work has pioneered novel strategies for high-dimensional feature selection and optimization in machine learning contexts. Another key area of his focus is underwater navigation and positioning, where he has introduced innovative models for enhancing gravity navigation accuracy. With a strong foundation in mathematics, Dr. Zhao combines theoretical rigor with practical applicability, ensuring that his research contributes both to academic knowledge and technological development. His recent work explores how optimization strategies can be integrated into real-time systems, with implications in robotics, autonomous navigation, and engineering design. By addressing complex computational problems, Dr. Zhao’s research plays a vital role in driving forward the capabilities of intelligent systems and adaptive algorithms.

Award and Honor

Dr. Shijie Zhao has earned multiple accolades in recognition of his impactful contributions to scientific research and innovation. He has received four prestigious research awards for his work in intelligent systems, mathematical optimization, and applied computational modeling. His leadership in various national and provincial research initiatives has further cemented his reputation as a top-tier researcher in his domain. In addition to these honors, he has held editorial and reviewer positions for over ten internationally recognized journals, including publications by IEEE, Springer, and Elsevier—an acknowledgment of his expertise and academic integrity. Dr. Zhao is also an active member of 13 professional bodies, reflecting his global engagement and scholarly influence. His participation in high-impact collaborative projects and his growing citation index underscore the recognition and respect he commands in the research community. These honors validate his innovative spirit and unwavering dedication to advancing knowledge in mathematics and intelligent computing.

Conclusion

In conclusion, Assoc. Prof. Dr. Shijie Zhao exemplifies excellence in mathematical research, optimization theory, and intelligent system applications. His educational background, combined with over a decade of professional experience, positions him as a thought leader in his field. Through pioneering contributions to metaheuristic algorithms, multi-objective optimization, and underwater navigation, he bridges the gap between theoretical frameworks and practical technologies. His commitment to research integrity, academic service, and innovation has earned him widespread recognition and professional accolades. As an educator, leader, and scientist, Dr. Zhao’s multifaceted contributions reflect a deep dedication to advancing scientific knowledge and solving complex global challenges. His future endeavors are poised to have even greater impacts on the fields of artificial intelligence, data-driven decision-making, and intelligent navigation. With a strong publication record, a solid foundation in mathematics, and an expanding research network, Dr. Zhao continues to be a prominent and influential figure in the global academic landscape.

Publications Top Notes

  • Title: ID2TM: A Novel Iterative Double-Cross Domain-Center Transfer-Matching Method for Underwater Gravity-Aided Navigation
    Authors: Shijie Zhao, Zhiyuan Dou, Huizhong Zhu, Wei Zheng, Yifan Shen
    Year: 2025
    Source: IEEE Internet of Things Journal

  • Title: OS-BiTP: Objective sorting-informed bidomain-information transfer prediction for dynamic multiobjective optimization
    Authors: Shijie Zhao, Tianran Zhang, Lei Zhang, Jinling Song
    Year: 2025
    Source: Swarm and Evolutionary Computation

  • Title: Mirage search optimization: Application to path planning and engineering design problems
    Authors: Jiahao He, Shijie Zhao, Jiayi Ding, Yiming Wang
    Year: 2025
    Source: Advances in Engineering Software

  • Title: Twin-population Multiple Knowledge-guided Transfer Prediction Framework for Evolutionary Dynamic Multi-Objective Optimization
    Authors: Shijie Zhao, Tianran Zhang, Miao Chen, Lei Zhang
    Year: 2025
    Source: Applied Soft Computing

  • Title: VC-TpMO: V-dominance and staged dynamic collaboration mechanism based on two-population for multi- and many-objective optimization algorithm
    Authors: Shijie Zhao, Shilin Ma, Tianran Zhang, Miao Chen
    Year: 2025
    Source: Expert Systems with Applications

  • Title: A Novel Cross-Line Adaptive Domain Matching Algorithm for Underwater Gravity Aided Navigation
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2024
    Source: IEEE Geoscience and Remote Sensing Letters

  • Title: Triangulation topology aggregation optimizer: A novel mathematics-based meta-heuristic algorithm for continuous optimization and engineering applications
    Authors: Shijie Zhao, Tianran Zhang, Liang Cai, Ronghua Yang
    Year: 2024
    Source: Expert Systems with Applications

  • Title: Improving Matching Efficiency and Out-of-Domain Positioning Reliability of Underwater Gravity Matching Navigation Based on a Novel Domain-Center Adaptive-Transfer Matching Method
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2023
    Source: IEEE Transactions on Instrumentation and Measurement

  • Title: A dynamic support ratio of selected feature-based information for feature selection
    Authors: Shijie Zhao, Mengchen Wang, Shilin Ma, Qianqian Cui
    Year: 2023
    Source: Engineering Applications of Artificial Intelligence

  • Title: Sea-horse optimizer: a novel nature-inspired meta-heuristic for global optimization problems
    Authors: Shijie Zhao, Tianran Zhang, Shilin Ma, Mengchen Wang
    Year: 2023
    Source: Applied Intelligence

  • Title: Improving the Out-of-Domain Matching Reliability and Positioning Accuracy of Underwater Gravity Matching Navigation Based on a Novel Cyclic Boundary Semisquare-Domain Researching Method
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2023
    Source: IEEE Sensors Journal

  • Title: A feature selection method via relevant-redundant weight
    Authors: Shijie Zhao, Mengchen Wang, Shilin Ma, Qianqian Cui
    Year: 2022
    Source: Expert Systems with Applications

  • Title: Dandelion Optimizer: A nature-inspired metaheuristic algorithm for engineering applications
    Authors: Shijie Zhao, Tianran Zhang, Shilin Ma, Miao Chen
    Year: 2022
    Source: Engineering Applications of Artificial Intelligence

  • Title: Improving Matching Efficiency and Out-of-domain Reliability of Underwater Gravity Matching Navigation Based on a Novel Soft-margin Local Semicircular-domain Re-searching Model
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2022
    Source: Remote Sensing

  • Title: Improving Matching Accuracy of Underwater Gravity Matching Navigation Based on Iterative Optimal Annulus Point Method with a Novel Grid Topology
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Aigong Xu, Huizhong Zhu
    Year: 2021
    Source: Remote Sensing

  • Title: A Novel Quantum Entanglement‐Inspired Meta‐heuristic Framework for Solving Multimodal Optimization Problems
    Authors: Shijie Zhao
    Year: 2021
    Source: Chinese Journal of Electronics

  • Title: A Novel Modified Tree‐Seed Algorithm for High‐Dimensional Optimization Problems
    Authors: Shijie Zhao
    Year: 2020
    Source: Chinese Journal of Electronics