A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers

This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that supp...

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Main Authors: Guo Li, Fei Lv, Xu Guan
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/894573
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spelling doaj-b5e18ed576e4498eb3f1980e71a1b59d2020-11-25T01:22:56ZengHindawi LimitedThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/894573894573A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple ManufacturersGuo Li0Fei Lv1Xu Guan2School of Management and Economics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Management, Huazhong University of Science and Technology, Wuhan 430074, ChinaEconomics and Management School, Wuhan University, Wuhan 430072, ChinaThis paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.http://dx.doi.org/10.1155/2014/894573
collection DOAJ
language English
format Article
sources DOAJ
author Guo Li
Fei Lv
Xu Guan
spellingShingle Guo Li
Fei Lv
Xu Guan
A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers
The Scientific World Journal
author_facet Guo Li
Fei Lv
Xu Guan
author_sort Guo Li
title A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers
title_short A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers
title_full A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers
title_fullStr A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers
title_full_unstemmed A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers
title_sort collaborative scheduling model for the supply-hub with multiple suppliers and multiple manufacturers
publisher Hindawi Limited
series The Scientific World Journal
issn 2356-6140
1537-744X
publishDate 2014-01-01
description This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.
url http://dx.doi.org/10.1155/2014/894573
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