A Decision-Making Tool for the Optimization of Empty Containers' Return in the Liner Shipping: Optimization by Using the Genetic Algorithm

A Decision-Making Tool for the Optimization of Empty Containers' Return in the Liner Shipping: Optimization by Using the Genetic Algorithm

Naima Belayachi (Laboratoire d'informatique d'Oran (LIO), University of Oran 1 Ahmed Ben Bella, Oran, Algeria), Fouzia Amrani (Ecole Nationale Polytechnique d'Oran (ENPO), Oran, Algeria) and Karim Bouamrane (Laboratoire d'informatique d'Oran (LIO), University of Oran 1 Ahmed Ben Bella, Oran, Algeria)
Copyright: © 2018 |Pages: 18
DOI: 10.4018/IJDSST.2018070103

Abstract

This article describes how in the maritime transportation sector, containerization represents one of the most remarkable improvements. In fact, the different shipping companies provide great efforts, whose purpose is to reduce the cost of this transport. However, these companies are facing a problem of empty containers, which are not available at some ports of Maritime Transport Network (MTN) to meet the clients' demands. This problem is simply a consequence of the imbalance in the distribution of containers through the MTN due to the set of containers that do not return to the origin port. This work offers a decision-making tool to this problem by proposing an optimal return of empty containers. The proposed application is based on evolutionary heuristics. Its principle is to find an optimal solution from a set of several feasible solutions generated during an initial population in order to enable the search of empty containers at lower cost.
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2. State Of Art

The key aspect of our research is situated within the framework of the activities of a shipping company owner of empty containers, which aims to minimize the cost of returning empty containers that represent a return flow in the transport logistics, whose purpose is to maximize the gain obtained on containers full transported in a merchandise shipping operation.

In order to concentrate on everything that is connected to this work, the authors propose the state of the art as follows on the return logistics and repositioning of empty containers.

A discrete-time linear analytical model was proposed by Hu et al. (2002), it consists of four critical activities: collection, storage, treatment, and distribution. The objective function allows to solve a minimization problem of the total cost of reverse logistics concerning the returned hazardous waste. Another model was proposed by Min et al. (2006), who used genetic algorithms to study the problem of the management of returned products. Also, Zhou et al. (2010) proposed a design of a reverse logistics network with a consideration of the repair and recovery options simultaneously. For this reason, a mathematical model of linear programming was proposed, where the objective function of the model is to minimize the total cost of the management of returned products.

On another side, Srivastava (2008) provided a design of a reverse logistics network, and he offered a three-level design (products returned by clients, collection centers, factories). He considered that the client is the source of the returned products. The proposed objective function is to maximize the profit, which is equal to revenues minus the sum of resales cost of reverse logistics and the price of resolution.

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