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Optimizing two-level reverse distribution networks with hybrid memetic algorithms

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.

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Notes

  1. 1.

    All results, solutions, instances, and figures are available online at http://www.alandefreitas.com/downloads/problem-instances.php.

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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.

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Correspondence to A. R. R. Freitas.

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Freitas, A.R.R., Silva, V.M.R., Campelo, F. et al. Optimizing two-level reverse distribution networks with hybrid memetic algorithms. Optim Lett 8, 753–762 (2014). https://doi.org/10.1007/s11590-013-0615-8

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Keywords

  • Evolutionary computation
  • Memetic algorithms
  • Reverse distribution networks
  • Logistics