A multi-affinity model for logistics network inspired by bio-system

Abstract

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.

A new integrated forward and reverse logistics model: A case study

“…These models include not only traditional logistic activities and flows, but also return channel activities. Hu and Sheng (2014) proposed a bio-inspired model in order to deal with large-scale logistics model. Designing the forward and reverse logistics should be integrated due to the fact that configuration of the reverse logistics network has a strong influence on the forward logistics network and vice versa (Lee and Dong, 2008).…”