Yuri Sotskov | Scheduling Theory | Best Researcher Award

Published on by Academic Awards

Prof. Yuri Sotskov | Scheduling Theory | Best Researcher Award

United Institute of Informatics Problems of the National Academy of Sciences of Belarus | Belarus

Prof. Yuri Sotskov is a leading researcher in applied mathematics, operations research, graph theory, and scheduling, with a prolific publication record exceeding 110 works, including scientific monographs, textbooks, and over 200 international journal and conference papers. His research focuses on optimization algorithms, combinatorial and permutation-based scheduling, differential evolution strategies, and multi-objective decision-making models, with applications in manufacturing, steelmaking, and complex production systems. Prof. Yuri Sotskov has contributed significant innovations in energy-efficient scheduling, hybrid job-shop optimization, and algorithmic approaches for multi-processor and multi-energy systems, demonstrating both theoretical depth and practical impact. His work has been widely recognized, reflected in 1,889 citations and an h-index of 26, and he serves on the editorial boards of multiple international journals. His sustained research productivity, influential publications, and advancements in algorithmic and mathematical modeling firmly establish him as a leading figure in his field, making him a highly deserving candidate for prestigious research recognition.

Profile: Scopus | Orcid

Featured Publications

  • Sotskov, Y. N., … (2026). An iterative greedy algorithm based on neighborhood search for energy-efficient scheduling of distributed permutation flowshop with sequence-dependent setup time. Expert Systems with Applications.

  • Sotskov, Y. N., … (2025). A review of dynamic flexible regulation strategies for multi-energy coupled steelmaking-continuous casting production. [Journal name unavailable].

  • Sotskov, Y. N., … (2025). Hierarchically controlled differential evolution algorithm. Expert Systems with Applications.

  • Sotskov, Y. N., … (2025). Diversity enhancement-based differential evolution with a novel perturbation strategy. Swarm and Evolutionary Computation.

  • Sotskov, Y. N., … (2025). Differential evolution based on individual information parameter setting and diversity measurement of aggregated distribution. Swarm and Evolutionary Computation.

Shin-Li Lu | Industrial Engineering | Best Researcher Award

Published on by Academic Awards

Prof. Shin-Li Lu | Industrial Engineering | Best Researcher Award

Prof. Shin-Li Lu | Chung Yuan Christian University | Taiwan

Prof. Shin-Li Lu is a distinguished Professor in the Department of Industrial and Systems Engineering and serves as Chairman of the Undergraduate Program at the College of Electrical Engineering and Computer Science, Chung Yuan Christian University. With extensive expertise in statistical process control, quality and production management, business intelligence, and big data analytics, Prof. Shin-Li Lu has made significant contributions to both academia and industry. He has held leadership roles including Dean of Management and Information and Chairman of Industrial Management and Enterprise Information, and has previously served as Professor and Associate Professor at Aletheia University. His prolific research includes numerous high-impact publications in SCI and EI-indexed journals on topics such as EWMA, GWMA control charts, economic-statistical design, and forecasting methods for manufacturing and energy systems. Prof. Shin-Li Lu has presented widely at international conferences, led multiple MOST-funded research projects, and contributes as an editor and reviewer for prominent journals, advancing sustainable industrial engineering, quality management, and statistical process monitoring.

Profile: Google Scholar

Featured Publications

Lu, S. L. (2015). An extended nonparametric exponentially weighted moving average sign control chart. Quality and Reliability Engineering International, 31(1), 3–13. [Cited by 84]

Lu, S. L. (2019). Integrating heuristic time series with modified grey forecasting for renewable energy in Taiwan. Renewable Energy, 133, 1436–1444. [Cited by 56]

Lu, S. L. (2018). Nonparametric double generally weighted moving average sign charts based on process proportion. Communications in Statistics – Theory and Methods, 47(11), 2684–2700. [Cited by 27]

Sheu, S. H., & Lu, S. L. (2009). Monitoring the mean of autocorrelated observations with one generally weighted moving average control chart. Journal of Statistical Computation and Simulation, 79(12), 1393–1406. [Cited by 26]

Huang, C. J., Tai, S. H., & Lu, S. L. (2014). Measuring the performance improvement of a double generally weighted moving average control chart. Expert Systems with Applications, 41(7), 3313–3322. [Cited by 24]