Genetic algorithms applied to reverse distribution networks

A. R.R. Freitas; V. M.R. Silva; F. G. Guimarães; F. Campelo

doi:10.1007/978-3-642-32922-7_33

Genetic algorithms applied to reverse distribution networks

A. R.R. Freitas^*, V. M.R. Silva, F. G. Guimarães, F. Campelo

^*Corresponding author for this work

College of Engineering and Physical Sciences

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

Reverse Distribution Networks are designed to plan the distribution of products from customers to manufacturers. In this paper, we study the problem with two-levels,with products transported from origination points to collection sites before being sent to a refurbishing site. The optimization of reverse distribution networks can reduce the costs of this reverse chain and help companies become more environmentally efficient. In this paper we describe heuristics for deciding locations, algorithms for defining routes, and problem-specific genetic operators. The results of a comparative analysis of 11 algorithms over 25 problem instances suggest that genetic algorithms hybridized with simplex routing algorithms were significantly better than the other approaches tested.

Original language	English
Title of host publication	Soft Computing Models in Industrial and Environmental Applications - 7th International Conference, SOCO'12
Publisher	Springer
Pages	317-326
Number of pages	10
ISBN (Print)	9783642329210
DOIs	https://doi.org/10.1007/978-3-642-32922-7_33
Publication status	Published - 1 Jan 2013
Event	7th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO'12 - Ostrava, Czech Republic Duration: 5 Sept 2012 → 7 Sept 2012

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	188 AISC
ISSN (Print)	2194-5357

Conference

Conference	7th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO'12
Country/Territory	Czech Republic
City	Ostrava
Period	5/09/12 → 7/09/12

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10.1007/978-3-642-32922-7_33

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Freitas, A. R. R., Silva, V. M. R., Guimarães, F. G., & Campelo, F. (2013). Genetic algorithms applied to reverse distribution networks. In Soft Computing Models in Industrial and Environmental Applications - 7th International Conference, SOCO'12 (pp. 317-326). (Advances in Intelligent Systems and Computing; Vol. 188 AISC). Springer. https://doi.org/10.1007/978-3-642-32922-7_33

@inproceedings{1b16af64603a458681745cf5e5a233b9,

title = "Genetic algorithms applied to reverse distribution networks",

abstract = "Reverse Distribution Networks are designed to plan the distribution of products from customers to manufacturers. In this paper, we study the problem with two-levels,with products transported from origination points to collection sites before being sent to a refurbishing site. The optimization of reverse distribution networks can reduce the costs of this reverse chain and help companies become more environmentally efficient. In this paper we describe heuristics for deciding locations, algorithms for defining routes, and problem-specific genetic operators. The results of a comparative analysis of 11 algorithms over 25 problem instances suggest that genetic algorithms hybridized with simplex routing algorithms were significantly better than the other approaches tested.",

author = "Freitas, {A. R.R.} and Silva, {V. M.R.} and Guimar{\~a}es, {F. G.} and F. Campelo",

year = "2013",

month = jan,

day = "1",

doi = "10.1007/978-3-642-32922-7_33",

language = "English",

isbn = "9783642329210",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer",

pages = "317--326",

booktitle = "Soft Computing Models in Industrial and Environmental Applications - 7th International Conference, SOCO'12",

address = "Germany",

note = "7th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO'12 ; Conference date: 05-09-2012 Through 07-09-2012",

}

Freitas, ARR, Silva, VMR, Guimarães, FG & Campelo, F 2013, Genetic algorithms applied to reverse distribution networks. in Soft Computing Models in Industrial and Environmental Applications - 7th International Conference, SOCO'12. Advances in Intelligent Systems and Computing, vol. 188 AISC, Springer, pp. 317-326, 7th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO'12, Ostrava, Czech Republic, 5/09/12. https://doi.org/10.1007/978-3-642-32922-7_33

Genetic algorithms applied to reverse distribution networks. / Freitas, A. R.R.; Silva, V. M.R.; Guimarães, F. G. et al.
Soft Computing Models in Industrial and Environmental Applications - 7th International Conference, SOCO'12. Springer, 2013. p. 317-326 (Advances in Intelligent Systems and Computing; Vol. 188 AISC).

Research output: Chapter in Book/Published conference output › Conference publication

TY - GEN

T1 - Genetic algorithms applied to reverse distribution networks

AU - Freitas, A. R.R.

AU - Silva, V. M.R.

AU - Guimarães, F. G.

AU - Campelo, F.

PY - 2013/1/1

Y1 - 2013/1/1

N2 - Reverse Distribution Networks are designed to plan the distribution of products from customers to manufacturers. In this paper, we study the problem with two-levels,with products transported from origination points to collection sites before being sent to a refurbishing site. The optimization of reverse distribution networks can reduce the costs of this reverse chain and help companies become more environmentally efficient. In this paper we describe heuristics for deciding locations, algorithms for defining routes, and problem-specific genetic operators. The results of a comparative analysis of 11 algorithms over 25 problem instances suggest that genetic algorithms hybridized with simplex routing algorithms were significantly better than the other approaches tested.

AB - Reverse Distribution Networks are designed to plan the distribution of products from customers to manufacturers. In this paper, we study the problem with two-levels,with products transported from origination points to collection sites before being sent to a refurbishing site. The optimization of reverse distribution networks can reduce the costs of this reverse chain and help companies become more environmentally efficient. In this paper we describe heuristics for deciding locations, algorithms for defining routes, and problem-specific genetic operators. The results of a comparative analysis of 11 algorithms over 25 problem instances suggest that genetic algorithms hybridized with simplex routing algorithms were significantly better than the other approaches tested.

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DO - 10.1007/978-3-642-32922-7_33

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AN - SCOPUS:84868281635

SN - 9783642329210

T3 - Advances in Intelligent Systems and Computing

SP - 317

EP - 326

BT - Soft Computing Models in Industrial and Environmental Applications - 7th International Conference, SOCO'12

PB - Springer

T2 - 7th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO'12

Y2 - 5 September 2012 through 7 September 2012

ER -

Genetic algorithms applied to reverse distribution networks

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