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

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.