The location-inventory model with risk pooling and split demand
In the traditional location-inventory system, every demand depot could be served by only one distribution center (DC). This paper relaxes the assumption. The demand depot could be split and served by more than one DC. First, based on the capacitated location-inventory model, the location-inventory m...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2019-01-01
|
Series: | Cogent Business & Management |
Subjects: | |
Online Access: | http://dx.doi.org/10.1080/23311975.2019.1691337 |
id |
doaj-d274d56c1e6a43219b9af708c8cadb4f |
---|---|
record_format |
Article |
spelling |
doaj-d274d56c1e6a43219b9af708c8cadb4f2021-07-15T13:47:57ZengTaylor & Francis GroupCogent Business & Management2331-19752019-01-016110.1080/23311975.2019.16913371691337The location-inventory model with risk pooling and split demandHao Xiong0Huili Yan1Hainan UniversityHainan UniversityIn the traditional location-inventory system, every demand depot could be served by only one distribution center (DC). This paper relaxes the assumption. The demand depot could be split and served by more than one DC. First, based on the capacitated location-inventory model, the location-inventory model with split demand is presented. Second, the advantage of permitting split and the properties of split are analyzed. Third, in order to solve this new model, a two-phase genetic heuristic algorithm with priority allocating method based on an approximate individual allocating cost are proposed. The results of numerical experiments are compared with non-split version and an important conclusion is illustrated: a small number of split points can make significant cost savings. The results of this study provide a useful reference for location-inventory decision.http://dx.doi.org/10.1080/23311975.2019.1691337location-inventorygenetic heuristic algorithmsplit demandsafety inventory |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hao Xiong Huili Yan |
spellingShingle |
Hao Xiong Huili Yan The location-inventory model with risk pooling and split demand Cogent Business & Management location-inventory genetic heuristic algorithm split demand safety inventory |
author_facet |
Hao Xiong Huili Yan |
author_sort |
Hao Xiong |
title |
The location-inventory model with risk pooling and split demand |
title_short |
The location-inventory model with risk pooling and split demand |
title_full |
The location-inventory model with risk pooling and split demand |
title_fullStr |
The location-inventory model with risk pooling and split demand |
title_full_unstemmed |
The location-inventory model with risk pooling and split demand |
title_sort |
location-inventory model with risk pooling and split demand |
publisher |
Taylor & Francis Group |
series |
Cogent Business & Management |
issn |
2331-1975 |
publishDate |
2019-01-01 |
description |
In the traditional location-inventory system, every demand depot could be served by only one distribution center (DC). This paper relaxes the assumption. The demand depot could be split and served by more than one DC. First, based on the capacitated location-inventory model, the location-inventory model with split demand is presented. Second, the advantage of permitting split and the properties of split are analyzed. Third, in order to solve this new model, a two-phase genetic heuristic algorithm with priority allocating method based on an approximate individual allocating cost are proposed. The results of numerical experiments are compared with non-split version and an important conclusion is illustrated: a small number of split points can make significant cost savings. The results of this study provide a useful reference for location-inventory decision. |
topic |
location-inventory genetic heuristic algorithm split demand safety inventory |
url |
http://dx.doi.org/10.1080/23311975.2019.1691337 |
work_keys_str_mv |
AT haoxiong thelocationinventorymodelwithriskpoolingandsplitdemand AT huiliyan thelocationinventorymodelwithriskpoolingandsplitdemand AT haoxiong locationinventorymodelwithriskpoolingandsplitdemand AT huiliyan locationinventorymodelwithriskpoolingandsplitdemand |
_version_ |
1721300618042146816 |