A Flexible Integrated Forward/ Reverse Logistics Model with Random Path-Based Memetic Algorithm

By Yadegari, Ehsan; Najmi, Hesamaddin et al. | Iranian Journal of Management Studies, April 2015 | Go to article overview

A Flexible Integrated Forward/ Reverse Logistics Model with Random Path-Based Memetic Algorithm


Yadegari, Ehsan, Najmi, Hesamaddin, Ghomi-Avili, Morteza, Zandieh, Mostafa, Iranian Journal of Management Studies


(ProQuest: ... denotes formulae omitted.)

Introduction

Extended producer responsibility is becoming more common across the world. Implementation of legislation, social responsibility, corporate imaging, environmental concern, economic benefits and customer awareness are forcing original equipment manufacturers (OEMs) to manufacture products that are environmentally friendly in order to contribute to the global large-scale effort towards environmental protection. One way of doing so is through the utilization of returned products, which extends their useful life cycle.

Products can be returned for reasons such as customer dissatisfaction and warranty. Such products can be sorted for reuse, remanufacture, recycle and disposal. In addition, industries are using remanufacturing for expensive products such as turbines used in airplane and electricity generation systems. In these cases, the recovery of used products is economically more attractive than disposal (Koh, Hwang, Sohn, & Ko, 2002).

One of the most important and strategic issues in supply chain management is the configuration of the logistics network having a significant effect on the total performance of the supply chain. The configuration of the reverse logistics network, however, has a strong influence on the performance of the forward logistics network, and vice versa, as they share a number of resources. Due to the fact that designing the forward and reverse logistics separately leads to sub-optimal designs with respect to strategic and tactical costs, the design of the forward and reverse logistics networks should be integrated (Fleischmann, Beullens, Bloemhof, Ruwaard, & Wassenhove, 2001; Lee & Dong, 2008; Verstrepen, Cruijssen, de Brito, & Dullaert, 2007).

Previous research in the area of forward, reverse and integrated logistics network design was often limited to the consideration of the flow to be transported between two consecutive stages. In other words, there is no flow between facilities that are not consecutive. Nevertheless, considering flows between facilities that are not consecutive will enhance logistics network efficiency and flexibility.

Based on the aforementioned considerations, this paper addresses the issue of flexible, integrated, multi-stage forward/reverse logistics network design including suppliers, production, distribution, collection/ inspection, recovery and disposal facilities with limited capacity. The rest of this paper is structured as follows:

Section 2 offers a literature review to assess the state-of-the-art in forward/reverse logistics network design. To design flexible integrated forward/reverse logistics networks, a generalized mixed integer linear programming (MILP) formulation is developed in sections 3 and 4. Section 5 presents an efficient MA using a dynamic search strategy to find solutions for large-scale problems. The computational performance of the metaheuristic algorithm is analyzed in Section 6. Section 7 concludes this paper and offers guidelines for further research.

Literature review

This section presents a brief review of the most relevant and recent literature in closed-loop supply chain network design problems followed by two tables in order to categorize this area based on network types and demonstrate some gaps in this research field.

Integrated forward and reverse logistics refers to all those activities associated with the transformation and flows of goods and services with their information from the sources of the materials to the end users. Dullaert et al. (2007) gave a general review of the supply chain design models to support the development of richer supply chain models. These models range from simple uncapacitated facility location models to complex capacitated multi-objective models aimed at determining the cost minimizing or profit maximizing system design.

In the context of reverse logistics, various models have been developed in the last decade. …

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