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: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2014/893851 |
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| _version_ | 1849682899343769600 |
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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 1607-887X |
| 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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