Multimodal Green Logistics Network Design of Urban Agglomeration with Stochastic Demand
This study investigates a multimodal green logistics network design problem of urban agglomeration with stochastic demand, in which different logistics authorities among the different cities jointly optimize the logistics node configurations and uniform carbon taxes over logistics transport modes to...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2019/4165942 |
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| _version_ | 1832564681461465088 |
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| author | Jiehui Jiang Dezhi Zhang Shuangyan Li Yajie Liu |
| author_facet | Jiehui Jiang Dezhi Zhang Shuangyan Li Yajie Liu |
| author_sort | Jiehui Jiang |
| collection | DOAJ |
| description | This study investigates a multimodal green logistics network design problem of urban agglomeration with stochastic demand, in which different logistics authorities among the different cities jointly optimize the logistics node configurations and uniform carbon taxes over logistics transport modes to maximize the total social welfare of urban agglomeration and consider logistics users’ choice behaviors. The users’ choice behaviors are captured by a logit-based stochastic equilibrium model. To describe the game behaviors of logistics authorities in urban agglomeration, the problem is formulated as two nonlinear bilevel programming models, namely, independent and centralized decision models. Next, a quantum-behaved particle swarm optimization (QPSO) embedded with a Method of Successive Averages (MSA) is presented to solve the proposed models. Simulation results show that to achieve the overall optimization layout of the green logistics network in urban agglomeration the logistics authorities should adopt centralized decisions, construct a multimode logistics network, and make a reasonable carbon tax. |
| format | Article |
| id | doaj-art-48344275272a414b98be6a17cb0d2c6d |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-48344275272a414b98be6a17cb0d2c6d2025-02-03T01:10:27ZengWileyJournal of Advanced Transportation0197-67292042-31952019-01-01201910.1155/2019/41659424165942Multimodal Green Logistics Network Design of Urban Agglomeration with Stochastic DemandJiehui Jiang0Dezhi Zhang1Shuangyan Li2Yajie Liu3School of Traffic & Transportation Engineering, Central South University, Changsha, Hunan 410075, ChinaSchool of Traffic & Transportation Engineering, Central South University, Changsha, Hunan 410075, ChinaCollege of Logistics and Transportation, Central South University of Forestry and Technology, Changsha, Hunan, 410004, ChinaCollege of System Engineering, National University of Defense Technology, Changsha, Hunan 410073, ChinaThis study investigates a multimodal green logistics network design problem of urban agglomeration with stochastic demand, in which different logistics authorities among the different cities jointly optimize the logistics node configurations and uniform carbon taxes over logistics transport modes to maximize the total social welfare of urban agglomeration and consider logistics users’ choice behaviors. The users’ choice behaviors are captured by a logit-based stochastic equilibrium model. To describe the game behaviors of logistics authorities in urban agglomeration, the problem is formulated as two nonlinear bilevel programming models, namely, independent and centralized decision models. Next, a quantum-behaved particle swarm optimization (QPSO) embedded with a Method of Successive Averages (MSA) is presented to solve the proposed models. Simulation results show that to achieve the overall optimization layout of the green logistics network in urban agglomeration the logistics authorities should adopt centralized decisions, construct a multimode logistics network, and make a reasonable carbon tax.http://dx.doi.org/10.1155/2019/4165942 |
| spellingShingle | Jiehui Jiang Dezhi Zhang Shuangyan Li Yajie Liu Multimodal Green Logistics Network Design of Urban Agglomeration with Stochastic Demand Journal of Advanced Transportation |
| title | Multimodal Green Logistics Network Design of Urban Agglomeration with Stochastic Demand |
| title_full | Multimodal Green Logistics Network Design of Urban Agglomeration with Stochastic Demand |
| title_fullStr | Multimodal Green Logistics Network Design of Urban Agglomeration with Stochastic Demand |
| title_full_unstemmed | Multimodal Green Logistics Network Design of Urban Agglomeration with Stochastic Demand |
| title_short | Multimodal Green Logistics Network Design of Urban Agglomeration with Stochastic Demand |
| title_sort | multimodal green logistics network design of urban agglomeration with stochastic demand |
| url | http://dx.doi.org/10.1155/2019/4165942 |
| work_keys_str_mv | AT jiehuijiang multimodalgreenlogisticsnetworkdesignofurbanagglomerationwithstochasticdemand AT dezhizhang multimodalgreenlogisticsnetworkdesignofurbanagglomerationwithstochasticdemand AT shuangyanli multimodalgreenlogisticsnetworkdesignofurbanagglomerationwithstochasticdemand AT yajieliu multimodalgreenlogisticsnetworkdesignofurbanagglomerationwithstochasticdemand |