Optimizing two-level reverse distribution networks with hybrid memetic algorithms

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

doi:10.1007/s11590-013-0615-8

Optimizing two-level reverse distribution networks with hybrid memetic algorithms

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

College of Engineering and Physical Sciences

Universidade Federal de Minas Gerais
Universidade Federal Fluminense

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

In a Two-Level Reverse Distribution Network, products are returned from customers to manufacturers through collection and refurbishing sites. The costs of the reverse chain often overtake the costs of the forward chain by many times. With some known algorithms for the problem as reference, we propose a hybrid memetic algorithm that uses linear programming and a heuristic for defining routes. Moreover, we describe heuristics for deciding locations, algorithms to define routes for the products, and problem-specific genetic operators. Memetic algorithms have returned the best results for all instances.

Original language	English
Pages (from-to)	753-762
Number of pages	10
Journal	Optimization Letters
Volume	8
Issue number	2
Early online date	14 Feb 2013
DOIs	https://doi.org/10.1007/s11590-013-0615-8
Publication status	Published - 1 Feb 2014

Funding

Acknowledgments This work has been supported by the Brazilian agencies CAPES, CNPq (Grants 472446/2010-0 and 305506/2010-2), and FAPEMIG (Grant APQ-04611-10); and by the Marie Curie International Research Staff Exchange Scheme Fellowship within the 7th European Community Framework Programme.

Keywords

Evolutionary computation
Logistics
Memetic algorithms
Reverse distribution networks

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10.1007/s11590-013-0615-8

Cite this

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AU - Silva, V. M R

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N2 - In a Two-Level Reverse Distribution Network, products are returned from customers to manufacturers through collection and refurbishing sites. The costs of the reverse chain often overtake the costs of the forward chain by many times. With some known algorithms for the problem as reference, we propose a hybrid memetic algorithm that uses linear programming and a heuristic for defining routes. Moreover, we describe heuristics for deciding locations, algorithms to define routes for the products, and problem-specific genetic operators. Memetic algorithms have returned the best results for all instances.

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KW - Evolutionary computation

KW - Logistics

KW - Memetic algorithms

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ER -

Optimizing two-level reverse distribution networks with hybrid memetic algorithms

Abstract

Funding

Keywords

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