Jingsheng Feng | Decision Sciences | Best Paper Award

Published on by Research Scientist

Mr. Jingsheng Feng | Decision Sciences | Best Paper Award

Research Assistant | Hefei University of Technology | China

Dr. Jingsheng Feng, a distinguished researcher at Hefei University of Technology, China, focuses on advanced logistics network optimization, supply chain resilience, and intelligent decision-making systems. His research integrates mathematical modeling, fuzzy logic, and multi-objective optimization to tackle complex challenges in customized logistics and industrial engineering. Notably, his work published in Computers & Industrial Engineering presents a reliable logistics network design model incorporating demand sensitivity to correlated disruptions, enhancing system robustness under uncertainty. In the International Journal of Systems Science: Operations & Logistics (, he co-developed disruption response strategy models for supplier selection and order allocation to support firms in maintaining operational stability during disruptions. His study in Expert Systems with Applications proposed fuzzy multi-objective team decision models for customer order decoupling point (CODP) and supplier selection, facilitating collaborative and data-driven decision-making in customized logistics supply chains. Additionally, his  work in Computers & Industrial Engineering explored battery swapping service network deployment, addressing behavioral factors such as driver range anxiety and impatience. Through his interdisciplinary contributions, Dr. Feng bridges theory and practice in logistics and supply chain engineering, promoting demand responsiveness, risk mitigation, and intelligent system design to advance sustainable, adaptive, and human-centered logistics strategies for modern industrial ecosystems. Her research impact is evident from 15 citations across 4 documents with an h-index of 2.

Profiles : ORCID | Scopus 

 

Featured Publications


1 .Feng, J., Hu, X., Xu, L., Luo, S., & Chen, J. (2025). Reliable logistics network design joint optimization problem applying demand sensitivity to correlated disruptions. Computers & Industrial Engineering.

2. Xu, L., Hu, X., Wu, Z., Luo, S., Feng, J., & Zhang, X. (2025). Disruption response strategy models for supplier selection and order allocation in customised logistics service supply chain. International Journal of Systems Science: Operations & Logistics.

3. Xu, L., Hu, X., Zhang, Y., Feng, J., & Luo, S. (2024). A fuzzy multiobjective team decision model for CODP and supplier selection in customized logistics service supply chain. Expert Systems with Applications, 213, 121387.

4. Hu, X., Zhang, X., Xu, L., Feng, J., & Luo, S. (2024). The battery swapping service network deployment problem: Impact of driver range anxiety and impatience. Computers & Industrial Engineering, 172, 110189.

Mehdi Ajalli | Decision Sciences | Best Researcher Award

Published on by Research Scientist

Assist. Prof. Dr. Mehdi Ajalli | Decision Sciences | Best Researcher Award

Faculty member | Bu-Ali Sina University | Iran

Dr. Mehdi Ajalli is an accomplished researcher and Assistant Professor in the Department of Management at Bu-Ali Sina University, specializing in industrial engineering, industrial management, and supply chain management, with particular expertise in decision-making techniques and fuzzy logic. He earned his Ph.D. and postdoctoral degree in industrial management from the University of Tehran and has been actively involved in research projects, including international collaborations. His professional experience includes teaching, mentorship, and academic leadership roles, contributing to student development and university initiatives. Dr. Ajalli has published more than 150 articles in prestigious journals indexed by Scopus, ScienceDirect, Springer, and ISC, and has presented his research at international conferences across Europe and Asia. His research interests focus on supply chain optimization, industrial management, and decision-making frameworks, integrating practical and theoretical approaches. He is recognized as a member of the National Foundation for Elites and Brilliant Talents of Iran and actively participates in academic and professional communities. His research skills encompass data analysis, modeling, decision analytics, and fuzzy logic applications, enabling him to address complex industrial and management challenges. His work has garnered 72 citations across 18 documents, with an h-index of 5, reflecting the recognition and impact of his contributions within the academic community.

Profile : Scopus

Featured Publication

1.A hybrid approach of CFA-FAHP-SWARA-ARAS for evaluating the readiness criteria of zinc industry green suppliers in blockchain technology adopting.