The structure of transportation networks determines the traffic flow characteristic of urban roads. In a case where demand and supply are fixed and given, the unevenly distributed traffic flow may lead to traffic congestion. Therefore, designing a rational urban transportation network (i.e., the urban transportation network design problem, UTNDP) has become one of the hottest topics in the transportation field. Due to the property of multi-objects, multi-constraints, and non-convexity, UTNDP is recognized as NP-Hard. Thus, many heuristic algorithms, based on biological laws or swarm intelligence, have been proposed in recent years. However, rare researches paid attention to the perfect topology of the leaf-vein network in nature. In this paper, a definitely new heuristic algorithm is proposed based on the leaf-vein network. By analyzing the growth process of leaf veins, the underlying relationship between urban transportation network and leaf-vein network is first investigated. An evolutionary mechanism of the algorithm or called the artificial leaf-vein generation rule, is then built by simulating the natural selection of biological evolution and genetic transmission. Given the differences between urban transportation networks and leaf-vein networks, a transformation method between the two networks is also designed. Finally, various experiments, including the Sioux Falls Network and China Motorways Network, are set up to demonstrate the performance of the proposed algorithm. The results show that, compared with conventional heuristic algorithms (e.g., GA, SA, and ACO), the proposed algorithm has superior performance and the high application potential in the reduction of the total travel time and length of the entire transportation network. The algorithm may help designers and planners optimize the urban transportation network and alleviate the negative effect of congestion in booming cities.
|Journal||International Journal of Bio-Inspired Computation|
|Publication status||Accepted/In press - 3 May 2021|