Knowledge Representation for the Model of Capacitated Vehicle Routing Problems

A knowledge representation - "GCS ternary" method for the model of capacitated vehicle routing problems (CVRP) was introduced on the basis of knowledge representation theories in artificial intelligence (AI) and knowledge engineering (KE) in order to decrease the deficiencies of model representation in decision support systems (DSS) for vehicle routing problems (VRP) in logistics distribution systems of e-commerce. The three parts of the representation in detail is G - graph that describes descriptive knowledge, C - constraints that describes controlling knowledge and S - search strategy that describes processing knowledge. The case study indicates that the representation can embody all knowledge needed in the process of solving CVRP, and its independent structure enhances the flexibility of the adaptation to different problems and can be used as reference by many DSS for VRP, which sets foundations for real-time scheduling and routing and can be extendedly used to DSS for many variants of VRP