Optimizing Transportation Network of Recovering End-of-Life Vehicles by Compromising Program in Polymorphic Uncertain Environment
With rapid development of technology and improvement of living standards, the per capita holding of automobiles greatly increases, and the amount of end-of-life vehicles (ELVs) becomes larger and larger such that it is valuable to investigate an effective strategy for recycling ELVs from the viewpoi...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2019/3894064 |
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| author | Jing Zhang Jingjing Liu Zhong Wan |
| author_facet | Jing Zhang Jingjing Liu Zhong Wan |
| author_sort | Jing Zhang |
| collection | DOAJ |
| description | With rapid development of technology and improvement of living standards, the per capita holding of automobiles greatly increases, and the amount of end-of-life vehicles (ELVs) becomes larger and larger such that it is valuable to investigate an effective strategy for recycling ELVs from the viewpoints of environmental protection and resource utilization. In this paper, an optimization model with fuzzy and stochastic parameters is built to formulate the transportation planning problems of recycling ELVs in polymorphic uncertain environment, where the unit processing and transportation costs, the selling price of reused items, and the fixed cost are all fuzzy, while the demand in secondary market and the production capacity are random owing to features underlying the practical data. For this complicated polymorphic uncertain optimization model, a unified compromising approach is proposed to hedge the uncertainty of this model such that some powerful optimization algorithms can be applied to make an optimal recycling plan. Then, an interactive algorithm is developed to find a compromising solution of the uncertain model. Numerical results show efficiency of the algorithm and a number of important managerial insights are revealed from the proposed model by scenario analysis and sensitivity analysis. |
| format | Article |
| id | doaj-art-59dd2bcef18440b88e46782bc8a965ba |
| 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-59dd2bcef18440b88e46782bc8a965ba2025-08-20T03:34:37ZengWileyJournal of Advanced Transportation0197-67292042-31952019-01-01201910.1155/2019/38940643894064Optimizing Transportation Network of Recovering End-of-Life Vehicles by Compromising Program in Polymorphic Uncertain EnvironmentJing Zhang0Jingjing Liu1Zhong Wan2Experimental Teaching Center, Guangdong University of Foreign Studies, Guangdong, Guangzhou, ChinaSchool of Mathematics and Statistics, Central South University, Changsha, ChinaSchool of Mathematics and Statistics, Central South University, Changsha, ChinaWith rapid development of technology and improvement of living standards, the per capita holding of automobiles greatly increases, and the amount of end-of-life vehicles (ELVs) becomes larger and larger such that it is valuable to investigate an effective strategy for recycling ELVs from the viewpoints of environmental protection and resource utilization. In this paper, an optimization model with fuzzy and stochastic parameters is built to formulate the transportation planning problems of recycling ELVs in polymorphic uncertain environment, where the unit processing and transportation costs, the selling price of reused items, and the fixed cost are all fuzzy, while the demand in secondary market and the production capacity are random owing to features underlying the practical data. For this complicated polymorphic uncertain optimization model, a unified compromising approach is proposed to hedge the uncertainty of this model such that some powerful optimization algorithms can be applied to make an optimal recycling plan. Then, an interactive algorithm is developed to find a compromising solution of the uncertain model. Numerical results show efficiency of the algorithm and a number of important managerial insights are revealed from the proposed model by scenario analysis and sensitivity analysis.http://dx.doi.org/10.1155/2019/3894064 |
| spellingShingle | Jing Zhang Jingjing Liu Zhong Wan Optimizing Transportation Network of Recovering End-of-Life Vehicles by Compromising Program in Polymorphic Uncertain Environment Journal of Advanced Transportation |
| title | Optimizing Transportation Network of Recovering End-of-Life Vehicles by Compromising Program in Polymorphic Uncertain Environment |
| title_full | Optimizing Transportation Network of Recovering End-of-Life Vehicles by Compromising Program in Polymorphic Uncertain Environment |
| title_fullStr | Optimizing Transportation Network of Recovering End-of-Life Vehicles by Compromising Program in Polymorphic Uncertain Environment |
| title_full_unstemmed | Optimizing Transportation Network of Recovering End-of-Life Vehicles by Compromising Program in Polymorphic Uncertain Environment |
| title_short | Optimizing Transportation Network of Recovering End-of-Life Vehicles by Compromising Program in Polymorphic Uncertain Environment |
| title_sort | optimizing transportation network of recovering end of life vehicles by compromising program in polymorphic uncertain environment |
| url | http://dx.doi.org/10.1155/2019/3894064 |
| work_keys_str_mv | AT jingzhang optimizingtransportationnetworkofrecoveringendoflifevehiclesbycompromisingprograminpolymorphicuncertainenvironment AT jingjingliu optimizingtransportationnetworkofrecoveringendoflifevehiclesbycompromisingprograminpolymorphicuncertainenvironment AT zhongwan optimizingtransportationnetworkofrecoveringendoflifevehiclesbycompromisingprograminpolymorphicuncertainenvironment |