Behavior-Preserving Top-Down Construction of Cross-Organization Emergency Response Processes

Cong Liu; Huiling Li; Qingtian Zeng; Qi Mo; MengChu Zhou; Long Cheng; Shangce Gao

doi:10.1109/JAS.2025.125537

Volume 12 Issue 12

Dec. 2025

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2025 > 12(12): 2513-2524

C. Liu, H. Li, Q. Zeng, Q. Mo, M. C. Zhou, L. Cheng, and S. Gao, “Behavior-preserving top-down construction of cross-organization emergency response processes,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 12, pp. 2513–2524, Dec. 2025. doi: 10.1109/JAS.2025.125537

Citation:

C. Liu, H. Li, Q. Zeng, Q. Mo, M. C. Zhou, L. Cheng, and S. Gao, “Behavior-preserving top-down construction of cross-organization emergency response processes,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 12, pp. 2513–2524, Dec. 2025. doi: 10.1109/JAS.2025.125537

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Behavior-Preserving Top-Down Construction of Cross-Organization Emergency Response Processes

doi: 10.1109/JAS.2025.125537

Funds: This work was supported in part by the National Natural Science Foundation of China (62472264, 52574256), the Natural Science Distinguished Youth Foundation of Shandong Province (ZR2025QA13), the Natural Science Key Basic Research Project of Shandong Province (ZR2025ZD17), the Taishan Scholar Program of Shandong Province (TSTP20250506), and National Funds through FCT (Fundação para a Ciência e a Tecnologia) (UID/04152/2025) – Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS (UID/PRR/04152/2025)

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Author Bio:
Cong Liu received the B.S. and the M.S. degree in computer software and theory from Shandong University of Science and Technology, in 2013 and 2015, respectively, the Ph.D. degree in computer science from the Department of Mathematics and Computer Science, Eindhoven University of Technology, 2019. He is an Invited Full Professor in the NOVA Information Management School, NOVA University of Lisbon, Portugal. His research interests are in the areas of process mining, business process management, and artificial intelligence

Huiling Li received the B.S. and M.S. degrees in computer science from Shandong University of Technology, in 2019 and 2022 respectively. She is currently a Ph.D. candidate in electrical engineering at the School of Electrical and Electronic Engineering, Shandong University of Technology. Her research interests are in the areas of Petri net and its applications

Qingtian Zeng received the B.S. and M.S. degrees in computer science from Shandong University of Science and Technology, in 1998 and 2001, respectively, and the Ph.D. degree in computer software and theory from the Institute of Computing Technology, Chinese Academy of Sciences, in 2005. He is currently a Professor with Shandong University of Science and Technology. His research interests are business process management, Petri nets, process mining, and emergency management

Qi Mo received the Ph.D. degree in software engineering from Yunnan University, in 2015. He is currently an Associate Professor at the School of Software, Yunnan University. His research interests include formal methods, software engineering, business process management, and emergency management

MengChu Zhou (Fellow, IEEE) received the Ph.D. degree in computer and systems engineering from Rensselaer Polytechnic Institute, USA in 1990. He joined New Jersey Institute of Technology (NJIT), USA in 1990, and is now a Distinguished Professor in electrical and computer engineering. His research interests are in Petri nets, intelligent automation, Internet of things, big data, web services, and intelligent transportation. He has 1400+ publications including 18 books, 900+ journal papers (700+ in IEEE Transactions), 32 patents and 32 book-chapters. His recently Co-Authored books include Intelligent Scheduling of Tasks for Cloud-Edge-Device Computing Systems, Wiley-IEEE Press, Hoboken, USA, 2025 (with B. Hu, Z. Cao, and M. Zhao), Learning Automata and their Applications to Intelligent Systems, Wiley-IEEE Press, Hoboken, USA, 2024 (with J. Zhang), and Device-Edge-Cloud Continuum Paradigms, Architectures and Applications, Springer Nature, 2023 (with C. Savaglio, G. Fortino, and J. Ma). He is a Life Member of Chinese Association for Science and Technology-USA and served as its President in 1999. He is a Fellow of International Federation of Automatic Control (IFAC), American Association for the Advancement of Science (AAAS), Chinese Association of Automation (CAA) and National Academy of Inventors (NAI)

Long Cheng received the Ph.D. degree in electronic engineering from National University of Ireland Maynooth, Ireland in 2014. He was an Assistant Professor at Dublin City University, and a Marie Curie Fellow at University College Dublin. He is a Professor with the School of Control and Computer Engineering, North China Electric Power University in Beijing. His research focuses on distributed systems and deep reinforcement learning. He has published more than 140 papers in journals and refereed conferences

Shangce Gao (Senior Member, IEEE) received the Ph.D. degree in innovative life science from University of Toyama, Japan in 2011. He is currently a Professor with the Faculty of Engineering, University of Toyama, Japan. His main research interests include mobile computing, nature-inspired technologies, and neural networks for optimization and real-world applications. He was a recipient of the Outstanding Academic Performance Award of IEICE, and the Outstanding Academic Achievement Award of IPSJ
Corresponding author: Cong Liu, e-mail: cliu@novaims.unl.pt; Huiling Li, e-mail: 19405020105@stumail.sdut.edu.cn
¹ We use correctness and soundness interchangeably in this paper.
Received Date: 2024-11-27
Revised Date: 2025-04-10
Accepted Date: 2025-05-27

Abstract

Abstract

When an emergency happens, one of the most important tasks is to perform effective emergency disposal. To this end, emergency organizations need to collaborate to accomplish missions that exceed the capacity of any single organization. Typically, an emergency disposal is structured as a set of collaborative processes, referred to as cross-organization emergency response processes (CERPs). To deliver better emergency services, the initial step is to construct a high-quality CERP model. This paper introduces a top-down CERP model construction approach to tackle one of the most challenging issues in this area: How to construct a CERP model such that each organization can design, change, and modify their own processes without disturbing the overall collaboration and correctness of CERP. The proposed top-down CERP model construction approach involves the following stages: 1) Cross-organization public process model construction; 2) Intra-organization public process model generation; 3) Behavior-preserving intra-organization private process model construction; and 4) Organization-specific CERP model construction. A case study on cross-organization fire emergency response is conducted to demonstrate the applicability and effectiveness of the proposed approach.
- Correctness and collaboration,
- cross-organization emergency disposal,
- emergency management,
- Petri nets,
- top-down construction

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¹ We use correctness and soundness interchangeably in this paper.

References(32)

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Behavior-Preserving Top-Down Construction of Cross-Organization Emergency Response Processes

doi: 10.1109/JAS.2025.125537

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