Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
EN
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EL
| URI: | http://purl.tuc.gr/dl/dias/95139AC5-AF6D-44FC-8FD5-951D37B5E968 | ||
| Έτος | 2022 | ||
| Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | ||
| Άδεια Χρήσης |
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| Βιβλιογραφική Αναφορά | T. Stamadianos, M. Marinaki, N. Matsatsinis and Y. Marinakis, “A hybridization of GRASP and UTASTAR for solving the vehicle routing problem with pickups and deliveries and 3D loading constraints,” in Learning and Intelligent Optimization, vol 13621, Lecture Notes in Computer Science, D. E. Simos, V. A. Rasskazova, F. Archetti, I. S. Kotsireas, P. M. Pardalos, Eds., Cham, Switzerland: Springer, 2022, pp. 505–520, doi: 10.1007/978-3-031-24866-5_36. https://doi.org/10.1007/978-3-031-24866-5_36 | ||
| Εμφανίζεται στις Συλλογές |
As urban centers grow, demand for goods transportation grows as well. The emergence of e-commerce has been a great catalyst, with online sales placing a big load on transportation companies. Current social conditions further amplify the effect. An unnoticed segment has been the delivery of large-size items in urban centers, where restrictions of different kinds impose the use of small vehicles. This research presents a novel combination of UTASTAR with Vehicle Routing Problem with Pickups and Deliveries and three-dimensional loading constraints to provide solutions. Scenarios of demand exceeding capacity are considered. A Decision Support System (DSS) is created to assist Decision Makers (DMs) of logistics companies get routing suggestions based on their priorities. The considerable size and weight of the items require careful handling of the smaller vehicles. The utilization of heuristic methods for routing expedites the solution process, enabling the formation of multiple solutions, which get ranked by the UTASTAR method on four criteria. The criteria values and thresholds are set indirectly by the DM. The model is tested on modified instances from the literature and a case study.
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