The Research on Low Carbon Logistics Routing Optimization Based on DNA-Ant Colony Algorithm. (22nd June 2014)

• Record Type: Journal Article
• Authors: Zhang, Liyi; Wang, Ying; Fei, Teng; Ren, Hongwei
• Other Names: Li Xiang Academic Editor.
• Is Part Of: Discrete dynamics in nature and society. Volume 2014(2014)
• Publication Date: 2014-06-22
• Subjects: System analysis -- Periodicals; Dynamics -- Periodicals; Chaotic behavior in systems -- Periodicals; Differentiable dynamical systems -- Periodicals; 003.05
• DOI: 10.1155/2014/893851
• Languages: English
• ISSNs: 1026-0226

Abstract

Abstract : As the energy conservation and emission reduction and sustainable development have become the hot topics in the world, low carbon issues catch more and more attention. Logistics, which is one of the important economic activities, plays a crucial role in the low carbon development. Logistics leads to some significant issues about consuming energy and carbon emissions. Therefore, reducing energy consumption and carbon emissions has become the inevitable trend for logistics industry. Low carbon logistics is introduced in these situations. In this paper, from the microcosmic aspects, we will bring the low carbon idea in the path optimization issues and change the amount of carbon emissions into carbon emissions cost to establish the path optimization model based on the optimization objectives of the lowest cost of carbon emissions. According to different levels of air pollution, we will establish the double objectives path optimization model with the consideration of carbon emissions cost and economy cost. Use DNA-ant colony algorithm to optimize and simulate the model. The simulation indicates that DNA-ant colony algorithm could find a more reasonable solution for low carbon logistics path optimization problems.