Volume 9 Number 2 (Feb. 2014)
Home > Archive > 2014 > Volume 9 Number 2 (Feb. 2014) >
JCP 2014 Vol.9(2): 285-294 ISSN: 1796-203X
doi: 10.4304/jcp.9.2.285-294

Exploring Ontology-driven Modeling Approach for Multi-agent Cooperation in Emergency Logistics

Li Zhang1, Dali Jiang1, Youjun Zeng2, Yahui Ning1, and Qianzhu Wang3
1Department of Logistical Information, Logistical Engineering University, Chongqing, China
2Department of Foreign Training, Logistical Engineering University, Chongqing, China
33G Academy, Chongqing University of Posts and Telecommunications, Chongqing, China


Abstract—Current emergency logistics strongly features geographical scatter, collaborative work and time priority. Although some models have been designed for application in emergency logistics, the knowledge heterogeneity in that field is still a major obstacle to intelligent cooperation. This study aims at applying ontology-based modeling approach to clearly represent the emergency logistics knowledge for decision optimization and multi-agent cooperation. An emergency logistics ontology representation model and ontology repository with Web Ontology Language (OWL) is developed through a five-layer modeling approach. This model allows multiple agents to share a clear and common understanding about the definition of emergency logistics problem and the semantics of exchanged emergency logistics knowledge. An extended ontology model with OWL format is designed in an illustrative example to represent a distribution routing problem in the relief work of 2008 Wenchuan Earthquake in China, and a rule-based intelligent reasoning application is implemented with the Jena ontology API supporting to validate the effectiveness of the proposed approach.

Index Terms—collaborative work, emergency logistics, ontology, reasoning, Multi-agent System (MAS)

[PDF]

Cite: Li Zhang, Dali Jiang, Youjun Zeng, Yahui Ning, and Qianzhu Wang, "Exploring Ontology-driven Modeling Approach for Multi-agent Cooperation in Emergency Logistics," Journal of Computers vol. 9, no. 2, pp. 285-294, 2014.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
  • Nov 14, 2019 News!

    Vol 14, No 11 has been published with online version   [Click]

  • Mar 20, 2020 News!

    Vol 15, No 2 has been published with online version   [Click]

  • Dec 16, 2019 News!

    Vol 14, No 12 has been published with online version   [Click]

  • Sep 16, 2019 News!

    Vol 14, No 9 has been published with online version   [Click]

  • Aug 16, 2019 News!

    Vol 14, No 8 has been published with online version   [Click]

  • Read more>>