Synergistic development model of population growth and infrastructure networks based on the slime mold network

Abstract

Developing efficient transportation infrastructure networks capable of accommodating increases in population and demand is essential in urban planning. The conventional approaches to urban planning involve simulations using mathematical models that incorporate temporal changes. The current models are often based on static factors like existing land and road networks. However, land use and road networks need to be adapted to environmental and systemic changes to better capture urban dynamics. In this study, we aimed to address this by proposing a novel synergistic development model of population growth and infrastructure networks inspired by the adaptive network formation of slime mold Physarum polycephalum. The proposed model builds on the Physarum solver by incorporating two dynamic processes: adding new source points and deleting sink points with low flow. Adding source points simulates population growth and increases infrastructure demand, whereas deleting sink points enhances network efficiency by removing redundant paths. The numerical simulations were conducted under various conditions to evaluate the effect of these processes on network formation. The results indicate that deleting sink points accelerates the convergence of the network by eliminating unnecessary paths. However, an increased flow can result in higher energy loss if the number of paths is insufficient. These findings indicate that adaptive feedback mechanisms, inspired by biological systems, play a crucial role in optimizing infrastructure networks in response to population growth, offering insights for flexible urban development strategies.