A Hybrid Approach to Solve a Model of Closed-Loop Supply Chain

This paper investigates a closed-loop supply chain network, including plants, demand centers, as well as collection centers, and disposal centers. In forward flow, the products are directly sent to demand centers, after being produced by plants, but in the reverse flow, reused products are returned...

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Main Authors: Nafiseh Tokhmehchi, Ahmad Makui, Soheil Sadi-Nezhad
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2015/179102
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spelling doaj-de91f1856b2f40eba61da02f3ae165712020-11-25T00:15:18ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/179102179102A Hybrid Approach to Solve a Model of Closed-Loop Supply ChainNafiseh Tokhmehchi0Ahmad Makui1Soheil Sadi-Nezhad2Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, IranDepartment of Industrial Engineering, Iran University of Science and Technology, Tehran, IranDepartment of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, IranThis paper investigates a closed-loop supply chain network, including plants, demand centers, as well as collection centers, and disposal centers. In forward flow, the products are directly sent to demand centers, after being produced by plants, but in the reverse flow, reused products are returned to collection centers and, after investigating, are partly sent to disposal centers and the other part is resent to plants for remanufacturing. The proposed mathematical model is based on mixed-integer programming and helps minimizing the total cost. Total costs include the expenditure of establishing new centers, producing new products, cargo transport in the network, and disposal. The model aims to answer these two questions. (1) What number and in which places the plants, collection centers, and disposal centers will be constructed. (2) What amount of products will be flowing in each segment of the chain, in order to minimize the total cost. Four types of tuned metaheuristic algorithms were used, which are hybrid forms of genetic and firefly algorithms. Finally an adequate number of instances are generated to analyse the behavior of proposed algorithms. Computational results reveal that iterative sequentialization hybrid provides better solution compared with the other approaches in large size.http://dx.doi.org/10.1155/2015/179102
collection DOAJ
language English
format Article
sources DOAJ
author Nafiseh Tokhmehchi
Ahmad Makui
Soheil Sadi-Nezhad
spellingShingle Nafiseh Tokhmehchi
Ahmad Makui
Soheil Sadi-Nezhad
A Hybrid Approach to Solve a Model of Closed-Loop Supply Chain
Mathematical Problems in Engineering
author_facet Nafiseh Tokhmehchi
Ahmad Makui
Soheil Sadi-Nezhad
author_sort Nafiseh Tokhmehchi
title A Hybrid Approach to Solve a Model of Closed-Loop Supply Chain
title_short A Hybrid Approach to Solve a Model of Closed-Loop Supply Chain
title_full A Hybrid Approach to Solve a Model of Closed-Loop Supply Chain
title_fullStr A Hybrid Approach to Solve a Model of Closed-Loop Supply Chain
title_full_unstemmed A Hybrid Approach to Solve a Model of Closed-Loop Supply Chain
title_sort hybrid approach to solve a model of closed-loop supply chain
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2015-01-01
description This paper investigates a closed-loop supply chain network, including plants, demand centers, as well as collection centers, and disposal centers. In forward flow, the products are directly sent to demand centers, after being produced by plants, but in the reverse flow, reused products are returned to collection centers and, after investigating, are partly sent to disposal centers and the other part is resent to plants for remanufacturing. The proposed mathematical model is based on mixed-integer programming and helps minimizing the total cost. Total costs include the expenditure of establishing new centers, producing new products, cargo transport in the network, and disposal. The model aims to answer these two questions. (1) What number and in which places the plants, collection centers, and disposal centers will be constructed. (2) What amount of products will be flowing in each segment of the chain, in order to minimize the total cost. Four types of tuned metaheuristic algorithms were used, which are hybrid forms of genetic and firefly algorithms. Finally an adequate number of instances are generated to analyse the behavior of proposed algorithms. Computational results reveal that iterative sequentialization hybrid provides better solution compared with the other approaches in large size.
url http://dx.doi.org/10.1155/2015/179102
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