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.
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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