A multi-affinity model for logistics network inspired by bio-system - Zhi-Hua Hu; Zhao-Han Sheng (International Journal of Computational Intelligence Systems, 2014)
How can we deal with the increasing scale of large logistics network for the booming economy? The structure, mechanisms and principles upon the logistics network show an evolutionary tendency which is complex, and interesting for designing and optimizing logistics network. The adaptability, stability and evolution capability are attractive for artificial intelligent systems. Inspired by biological systems, the metaphors for the structure and eight primary mechanisms are extracted to design a multi-affinity model for bio-inspired logistics network. Then, by mapping the biological elements and functions to logistics network, the evolutionary structure and simulation approach for logistics network are proposed and investigated by experiments. It is a novel way to study the complexity of logistics network and it is an interesting bionic approach for artificial network model. The research result can be employed to study the emergency features and collective behavior of large-scale logistics network.