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...

Full description

Saved in:
Bibliographic Details
Main Authors: Jing Zhang, Jingjing Liu, Zhong Wan
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2019/3894064
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849411911257423872
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