The Research on Low Carbon Logistics Routing Optimization Based on DNA-Ant Colony Algorithm

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...

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Main Authors: Liyi Zhang, Ying Wang, Teng Fei, Hongwei Ren
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2014/893851
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author Liyi Zhang
Ying Wang
Teng Fei
Hongwei Ren
author_facet Liyi Zhang
Ying Wang
Teng Fei
Hongwei Ren
author_sort Liyi Zhang
collection DOAJ
description 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.
format Article
id doaj-art-c99f10088a134cdaad109efdb1808e3e
institution DOAJ
issn 1026-0226
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language English
publishDate 2014-01-01
publisher Wiley
record_format Article
series Discrete Dynamics in Nature and Society
spelling doaj-art-c99f10088a134cdaad109efdb1808e3e2025-08-20T03:24:03ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2014-01-01201410.1155/2014/893851893851The Research on Low Carbon Logistics Routing Optimization Based on DNA-Ant Colony AlgorithmLiyi Zhang0Ying Wang1Teng Fei2Hongwei Ren3Information Engineering College, Tianjin University of Commerce, Tianjin 300134, ChinaEconomic College, Tianjin University of Commerce, Tianjin 300134, ChinaInformation Engineering College, Tianjin University of Commerce, Tianjin 300134, ChinaWaston Engineering Shool, State University of New York at Binghamton, 138 Conklin Avenue, Binghamton, NY 13902, USAAs 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.http://dx.doi.org/10.1155/2014/893851
spellingShingle Liyi Zhang
Ying Wang
Teng Fei
Hongwei Ren
The Research on Low Carbon Logistics Routing Optimization Based on DNA-Ant Colony Algorithm
Discrete Dynamics in Nature and Society
title The Research on Low Carbon Logistics Routing Optimization Based on DNA-Ant Colony Algorithm
title_full The Research on Low Carbon Logistics Routing Optimization Based on DNA-Ant Colony Algorithm
title_fullStr The Research on Low Carbon Logistics Routing Optimization Based on DNA-Ant Colony Algorithm
title_full_unstemmed The Research on Low Carbon Logistics Routing Optimization Based on DNA-Ant Colony Algorithm
title_short The Research on Low Carbon Logistics Routing Optimization Based on DNA-Ant Colony Algorithm
title_sort research on low carbon logistics routing optimization based on dna ant colony algorithm
url http://dx.doi.org/10.1155/2014/893851
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