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Journal of Engineering and Applied Sciences

ISSN: Online 1818-7803
ISSN: Print 1816-949x
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Locating Nearby Delivery Zones in an Urban Logistics Context

Dkhissi Btissam, Miloudi Ahmed and El Fellahi Abdelilah
Page: 8243-8253 | Received 21 Sep 2022, Published online: 21 Sep 2022

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Abstract

In logistics engineering, the client satisfaction is one of the most important stakes that a provider has to overcome. Thus, many research focused on developing the tools required to guarantee the client satisfaction taking into consideration the optimization of the costs. In this research and in addition to that two concerns (client satisfaction and costs optimization), we will examine establishing new nearby delivery zones close to major retail and commercial precincts in a socio-environmental context. Two alternatives is then available, modeling the real life problem as multiple depot vehicle routing problem or using the uncapacited sing hub location problem. In this study, we showed that the second alternative stands good than the first. Then, nearby delivery zones would be implemented in cities. These delivery zones will occupy sections of curbsides space and alleys to provide space for carriers to park their delivery vehicles in a pre-booked space where they can load/unload products for the delivery/pickup to neighboring businesses walking or using rolling carts. Hence, carriers will avoid time windows restriction by making a single long stop in the nearby delivery zone instead of driving around the city center from one destination to another. In this study, we provide a mathematical formulation to this end based on the uncapacitated single allocation p-hub location problem, also, a Genetic algorithm approach is presented. The performance of the model and the metaheuristic was tested using the Australian Post (AP) data set.


How to cite this article:

Dkhissi Btissam, Miloudi Ahmed and El Fellahi Abdelilah. Locating Nearby Delivery Zones in an Urban Logistics Context.
DOI: https://doi.org/10.36478/jeasci.2019.8243.8253
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2019.8243.8253