Title: Artificial leaf-vein network optimisation algorithm for urban transportation network design

Authors: Baozhen Yao; Chao Chen; Wenxuan Shan; Bin Yu

Addresses: State Key Laboratory of Structural Analysis for Industrial Equipment, School of Automotive Engineering, Dalian University of Technology, Dalian, 116024, China ' State Key Laboratory of Structural Analysis for Industrial Equipment, School of Automotive Engineering, Dalian University of Technology, Dalian, 116024, China ' School of Transportation Science and Engineering, Beihang University, Beijing, 100191, China ' School of Transportation Science and Engineering, Beihang University, Beijing, 100191, China

Abstract: Designing a rational urban transportation network has become one of the hottest topics in the transportation field. 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 analysing 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 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, a benchmark instance, the Sioux Falls network, is set up to demonstrate the performance of the proposed algorithm.

Keywords: urban transportation network design problem; UTNDP; artificial leaf-vein network; heuristic algorithm; auxin transport.

DOI: 10.1504/IJBIC.2022.128094

International Journal of Bio-Inspired Computation, 2022 Vol.20 No.4, pp.256 - 268

Received: 30 Aug 2020
Accepted: 20 May 2021

Published online: 05 Jan 2023 *

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