Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

Green Vehicle Routing Optimization Based on Carbon Emission and Multiobjective Hybrid Quantum Immune Algorithm

Liu, XH, Shan, MY, Zhang, RL and Zhang, L (2018) Green Vehicle Routing Optimization Based on Carbon Emission and Multiobjective Hybrid Quantum Immune Algorithm. Mathematical Problems in Engineering, 2018. ISSN 1024-123X

[img]
Preview
Text
8961505.pdf - Published Version
Available under License Creative Commons Attribution.

Download (2MB) | Preview

Abstract

© 2018 Xiao-Hong Liu et al. Green Vehicle Routing Optimization Problem (GVROP) is currently a scientific research problem that takes into account the environmental impact and resource efficiency. Therefore, the optimal allocation of resources and the carbon emission in GVROP are becoming more and more important. In order to improve the delivery efficiency and reduce the cost of distribution requirements through intelligent optimization method, a novel multiobjective hybrid quantum immune algorithm based on cloud model (C-HQIA) is put forward. Simultaneously, the computational results have proved that the C-HQIA is an efficient algorithm for the GVROP. We also found that the parameter optimization of the C-HQIA is related to the types of artificial intelligence algorithms. Consequently, the GVROP and the C-HQIA have important theoretical and practical significance.

Item Type: Article
Uncontrolled Keywords: 01 Mathematical Sciences, 09 Engineering
Subjects: H Social Sciences > HE Transportation and Communications
Divisions: Liverpool Business School
Publisher: Hindawi
Date Deposited: 11 Jul 2018 12:09
Last Modified: 11 Jul 2018 12:09
DOI or Identification number: 10.1155/2018/8961505
URI: http://researchonline.ljmu.ac.uk/id/eprint/8944

Actions (login required)

View Item View Item