An Artificial Immune Algorithm for a Closed-Loop Supply Chain Network Design Problem with Different Delivery Paths

An Artificial Immune Algorithm for a Closed-Loop Supply Chain Network Design Problem with Different Delivery Paths

Ehsan Yadegari, Mostafa Ekhtiari, Mostafa Zandieh, Akbar Alem-Tabriz
Copyright: © 2014 |Pages: 20
DOI: 10.4018/ijsds.2014070102
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Abstract

The concern about customer satisfaction and transportation cost in the business environment has spurred an interest in designing a flexible logistics network. This paper proposes a multi-delivery path closed-loop supply chain network to find not only the most cost efficient network design but also the best path to deliver the products to customers. To tackle with such an NP-hard problem an Artificial Immune Algorithm (AIA) is modified. To show the efficiency and accuracy of the proposed method numerical experiments are conducted. Consequently, the computational results validate the quality of the proposed approach by comparing them with those of obtained with exact methods.
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Literature Review

In this section, we relate our work with the existing literature by discussing the features comprised by the new model we propose in Section 3. In particular, we analyze the extent to which such features have been addressed in the literature.

Integrated forward and reverse logistics refers to all those activities associated with the transformation and the flows of goods and services with their information from the sources of the materials to the end users. (Dullaert, Bräysy, Goetschalckx, Raa, & Center, 2007) give a general review of the supply chain design models to support the development of richer supply chain models, capable of taking into account all logistics costs. These models range from simple un-capacitated facility location models to complex capacitated multi-objective models aimed at determining the cost minimizing or profit maximizing system design.

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