Managing Emergency Material Distribution Knowledge Using Ontology-Based Modeling for Emergency Distribution Decision

Abstract

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.

A survey on supply chain ontologies

“…Although in the field of Supply Chain there is not much research work on ontologies, as it comparatively happens in medicine, biology, telecommunications, etc., yet, there are some notable works, the study of which led to important conclusions. In particular, many scholars attempted the creation, extension and integration of ontologies into already existing models and many individual ontologies have been adapted to the field of Supply Chain Management and, particularly, in the field of Supply Chain planning (Chandra and Tumanyan, 2007), in the area of production, design, product manufacturing and product lifecycle management (Obitko and Marík, 2002;Huang et al, 2005;Lemaignan et al, 2006;Lin and Harding, 2007;Hepp, 2008;Bruno et al, 2015) or storage planning (Weber et al, 2019), in the sector of negotiations in the global manufacturing (Jiao et al, 2006) or in the area of suppliers and transport providers (Achatbi et al, 2018), in e-commerce (Tamma et al, 2005;Cao et al, 2015), in the field of transport, national or cross-border (Merdan et al, 2008;Ponanan et al, 2017;Dorofeev et al, 2020), in the domain of cooperation of 3PL companies in transport (Memon et al, 2014), in the field of Co-operative Supply System (Smirnov and Chandra, 2000), in the field of providing logistics services (Glöckner et al, 2017), in decision-making (Ha et al, 2008;Muñoz et al, 2011), for supplier selection (Yiqing et al, 2009), for waste treatment (Muñoz et al, 2013) or for emergency logistics distribution cases (Zhang, 2013), in the field of product tracking (Vikram et al, 2003), of delivery service management in logistics (Sivamani et al, 2014), of monitoring business partners in a supply network (Yu-Liang, 2010), in the field of e-business, e-commerce and e-logistics in general (Haugen and McCarthy, 2000;Ontoweb Ontology-Based Information, 2002;Foxvog and Bussler, 2005;…”

Exploring Agent-Based Modeling for Emergency Logistics Collaborative Decision Making

“…In this MAS model, the ontology modeling is introduced as the knowledge representation to describe public concepts concerning the emergency logistics process such as the environment, climate, and resources, etc. The specific ontology-based modeling method for emergency logistics is indicated in[10]. perspective, top level view and local level view.…”