Aiming at the requirements of urgency and dynamics in emergency logistics, this paper presents a multi-agent system (MAS) concept model for emergency logistics collaborative decision making. The suggested model includes three kinds of agents, i.e., role agent, function agent and assistant agent. Role agent excutes emergency logistics activities, function agent achieves the task requirements in every work phase and assistant agent helps organizing and visiting data. Two levels agent views serve as the basic skeleton of the MAS. Top level is the global decision-making view, which describes the task distribution process with multiple agents. Local level is the execution planning view, which simulates task executing process of the performer. Finally, an extended BDI agent structure model is proposed to help the implementation at application level.
Aiming at the knowledge representation problem in emergency logistics, this paper presents an ontology-based modeling framework for emergency distribution decision. The suggested ontology model includes the meta-ontology, the domain ontology and the upper relationship, and it can be extended to meet the various requirements in emergency logistics application. As an illustrative example, an instance of Location Routing Problem (LRP) is defined using proposed ontology model, and a rule-based reasoning experiment is developed with Jena. The result of experiment demonstrates the effectiveness of the ontology modeling framework, which can be used as an important complement to traditional optimization methods for emergency distribution decision.
Currently, the decision making of emergency logistics is faced with increasing challenges caused by deficient information, uncertain requirement and shortest response time. Agent-based modeling and multi-agent system have been proved as a promising ways in this field. Based on the previous work of emergency logistics decision framework, this paper presents a detailed design of agent internal structure of the emergency logistics multi-agent system. Some typical agents, such as logistics entity agent, task distribution agent and ontology visiting agent, are discussed from the composed function modules to the specific implementation. As the illustrative examples, the design of these primary agents can characterizes the basic structure of another agent in the emergency logistics multi-agent system, and it will be considered as the effective reference for system implementation.
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