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A viability study of pickup and delivery locations using genetic algorithm in intelligent transportation systems

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Abstract
Due to the increasing popularity of e-commerce and retail warehouses, city center retailers are having a rough time. This translates into a decreasing trend in city visitors and consequently, in retailers. Shop&Hop, established in the city of Ghent, wanted to address this phenomenon. The main purpose of the concept is to attract more people to shop in Ghent. Shop&Hop makes it possible for shoppers to leave their shopping bag in the store where they just made a purchase, after which the bag is transported to the desired parking lot. Unfortunately, the concept did not reach the hoped-for success and it was put on hold. The aim of this work is to analyze to what extent the operational choices, inherent to the original concept, affect the viability of this initiative. In this way, adaptions, which could increase the chance on viability, can be formulated. By relying on methods from the field of Operations Research, a mathematical model formulation and an accompanying genetic algorithm are developed and validated. During the subsequent viability study, two operational aspects are studied. First, the influence of the spatiality of the concept is mapped. Second, the impact of delivery time differentiation is studied. The viability study has shown that a concept, implementing aggregated pickup points, park-and-rides as delivery points and delivery time differentiation, has an increased chance on viability, compared to the original concept. Finally, it could be concluded that a Shop&Hop implementation in a certain city is heavily dependent on the urban planning of the city regarding park-and-ride locations.

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MLA
Lucq, Delphine, et al. “A Viability Study of Pickup and Delivery Locations Using Genetic Algorithm in Intelligent Transportation Systems.” INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 4, INTELLISYS 2023, edited by Kohei Arai, vol. 825, Springer, 2024, pp. 847–61, doi:10.1007/978-3-031-47718-8_54.
APA
Lucq, D., Lopez, A. J., Aghezzaf, E.-H., Semanjski, I., & Gautama, S. (2024). A viability study of pickup and delivery locations using genetic algorithm in intelligent transportation systems. In K. Arai (Ed.), INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 4, INTELLISYS 2023 (Vol. 825, pp. 847–861). https://doi.org/10.1007/978-3-031-47718-8_54
Chicago author-date
Lucq, Delphine, Angel J. Lopez, El-Houssaine Aghezzaf, Ivana Semanjski, and Sidharta Gautama. 2024. “A Viability Study of Pickup and Delivery Locations Using Genetic Algorithm in Intelligent Transportation Systems.” In INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 4, INTELLISYS 2023, edited by Kohei Arai, 825:847–61. Springer. https://doi.org/10.1007/978-3-031-47718-8_54.
Chicago author-date (all authors)
Lucq, Delphine, Angel J. Lopez, El-Houssaine Aghezzaf, Ivana Semanjski, and Sidharta Gautama. 2024. “A Viability Study of Pickup and Delivery Locations Using Genetic Algorithm in Intelligent Transportation Systems.” In INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 4, INTELLISYS 2023, ed by. Kohei Arai, 825:847–861. Springer. doi:10.1007/978-3-031-47718-8_54.
Vancouver
1.
Lucq D, Lopez AJ, Aghezzaf E-H, Semanjski I, Gautama S. A viability study of pickup and delivery locations using genetic algorithm in intelligent transportation systems. In: Arai K, editor. INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 4, INTELLISYS 2023. Springer; 2024. p. 847–61.
IEEE
[1]
D. Lucq, A. J. Lopez, E.-H. Aghezzaf, I. Semanjski, and S. Gautama, “A viability study of pickup and delivery locations using genetic algorithm in intelligent transportation systems,” in INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 4, INTELLISYS 2023, Amsterdam, the Netherlands, 2024, vol. 825, pp. 847–861.
@inproceedings{01HE02ZAJ6FAQBJ4PZM010K9B7,
  abstract     = {{Due to the increasing popularity of e-commerce and retail warehouses, city center retailers are having a rough time. This translates into a decreasing trend in city visitors and consequently, in retailers. Shop&Hop, established in the city of Ghent, wanted to address this phenomenon. The main purpose of the concept is to attract more people to shop in Ghent. Shop&Hop makes it possible for shoppers to leave their shopping bag in the store where they just made a purchase, after which the bag is transported to the desired parking lot. Unfortunately, the concept did not reach the hoped-for success and it was put on hold. The aim of this work is to analyze to what extent the operational choices, inherent to the original concept, affect the viability of this initiative. In this way, adaptions, which could increase the chance on viability, can be formulated. By relying on methods from the field of Operations Research, a mathematical model formulation and an accompanying genetic algorithm are developed and validated. During the subsequent viability study, two operational aspects are studied. First, the influence of the spatiality of the concept is mapped. Second, the impact of delivery time differentiation is studied. The viability study has shown that a concept, implementing aggregated pickup points, park-and-rides as delivery points and delivery time differentiation, has an increased chance on viability, compared to the original concept. Finally, it could be concluded that a Shop&Hop implementation in a certain city is heavily dependent on the urban planning of the city regarding park-and-ride locations.}},
  author       = {{Lucq, Delphine and Lopez, Angel J. and Aghezzaf, El-Houssaine and Semanjski, Ivana and Gautama, Sidharta}},
  booktitle    = {{INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 4, INTELLISYS 2023}},
  editor       = {{Arai, Kohei}},
  isbn         = {{9783031477171}},
  issn         = {{2367-3370}},
  language     = {{eng}},
  location     = {{Amsterdam, the Netherlands}},
  pages        = {{847--861}},
  publisher    = {{Springer}},
  title        = {{A viability study of pickup and delivery locations using genetic algorithm in intelligent transportation systems}},
  url          = {{http://doi.org/10.1007/978-3-031-47718-8_54}},
  volume       = {{825}},
  year         = {{2024}},
}

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