A GENETIC ALGORITHM FOR A MULTI-PRODUCT DISTRIBUTION PROBLEM
This paper addresses a distribution problem involving a set of different products that need to be distributed among a set of geographically disperse retailers and transported from the single warehouse to the aforementioned retailers. The distribution and transportation are made in order to satisfy r...
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Center for Quality, Faculty of Engineering, University of Kragujevac, Serbia
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doaj-5d9df2c3eabd48e8a77dc40ec552ead72021-04-02T12:07:27ZengCenter for Quality, Faculty of Engineering, University of Kragujevac, SerbiaInternational Journal for Quality Research1800-64501800-74732019-12-0113490191410.24874/IJQR13.04-11A GENETIC ALGORITHM FOR A MULTI-PRODUCT DISTRIBUTION PROBLEMBruno Cretú0Dalila B. M. M. Fontes1Seyed Mahdi Homayouni2Faculdade de Economia da Universidade do Porto, Porto, PortugalFaculdade de Economia da Universidade do Porto, Porto, Portugal; LIAAD- INESC TEC, Porto, PortugalLIAAD- INESC TEC, Porto, Portugal; Department of Industrial Engineering, Lenjan Branch, Islamic Azad University, Esfahan, IranThis paper addresses a distribution problem involving a set of different products that need to be distributed among a set of geographically disperse retailers and transported from the single warehouse to the aforementioned retailers. The distribution and transportation are made in order to satisfy retailers' demand while satisfying storage limits at both the warehouse and the retailers, transportation limits between the warehouse and the retailers, and other operational constraints. This problem is combinatorial in nature as it involves the assignment of a discrete finite set of objects, while satisfying a given set of conditions. Hence, we propose a genetic algorithm that is capable of finding good quality solutions. The genetic algorithm proposed is used to a real case study involving the distribution of eight products among 108 retailers from a single warehouse. The results obtained improve on those of company's current practice by achieving a cost reduction of about 13%.http://ijqr.net/journal/v13-n4/11.pdfgenetic algorithmsmulti-productdistribution problem |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Bruno Cretú Dalila B. M. M. Fontes Seyed Mahdi Homayouni |
spellingShingle |
Bruno Cretú Dalila B. M. M. Fontes Seyed Mahdi Homayouni A GENETIC ALGORITHM FOR A MULTI-PRODUCT DISTRIBUTION PROBLEM International Journal for Quality Research genetic algorithms multi-product distribution problem |
author_facet |
Bruno Cretú Dalila B. M. M. Fontes Seyed Mahdi Homayouni |
author_sort |
Bruno Cretú |
title |
A GENETIC ALGORITHM FOR A MULTI-PRODUCT DISTRIBUTION PROBLEM |
title_short |
A GENETIC ALGORITHM FOR A MULTI-PRODUCT DISTRIBUTION PROBLEM |
title_full |
A GENETIC ALGORITHM FOR A MULTI-PRODUCT DISTRIBUTION PROBLEM |
title_fullStr |
A GENETIC ALGORITHM FOR A MULTI-PRODUCT DISTRIBUTION PROBLEM |
title_full_unstemmed |
A GENETIC ALGORITHM FOR A MULTI-PRODUCT DISTRIBUTION PROBLEM |
title_sort |
genetic algorithm for a multi-product distribution problem |
publisher |
Center for Quality, Faculty of Engineering, University of Kragujevac, Serbia |
series |
International Journal for Quality Research |
issn |
1800-6450 1800-7473 |
publishDate |
2019-12-01 |
description |
This paper addresses a distribution problem involving a set of different products that need to be distributed among a set of geographically disperse retailers and transported from the single warehouse to the aforementioned retailers. The distribution and transportation are made in order to satisfy retailers' demand while satisfying storage limits at both the warehouse and the retailers, transportation limits between the warehouse and the retailers, and other operational constraints. This problem is combinatorial in nature as it involves the assignment of a discrete finite set of objects, while satisfying a given set of conditions. Hence, we propose a genetic algorithm that is capable of finding good quality solutions. The genetic algorithm proposed is used to a real case study involving the distribution of eight products among 108 retailers from a single warehouse. The results obtained improve on those of company's current practice by achieving a cost reduction of about 13%. |
topic |
genetic algorithms multi-product distribution problem |
url |
http://ijqr.net/journal/v13-n4/11.pdf |
work_keys_str_mv |
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