Complex network approach for the structural optimization of global crude oil trade system

It is essential to reveal the optimal structure of global crude oil supply and demand, which has become one of the most important factors affecting every country's energy strategy and economic development. However, the existing crude oil supply and demand structure does not function well. This paper proposes a distributed bipartite network to model crude oil trade. The optimal network structure, which has the minimal total trade cost is obtained by Simulated Annealing Algorithm. The presented optimization model encompasses the framework of complex network theory and crude oil trading issues, providing a good solution for the crude oil trade system. Comparing with the pre-optimized trading network, the proposed model can effectively reduce trade cost. The Robustness Indicator is proposed to reveal that the major oil-exporting countries choose their partners more wisely and the trade relations are steadier. In the optimal distributed network, both the major oil-exporting countries and major oil-importing countries play important roles in distributing crude oil among the trading countries. Overall, the proposed model offers fresh insights for structural reconstruction of crude oil supply and demand network centered on the efficient usage of crude oil and keeping the international oil trade running smoothly.