Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11851/8654
Title: | Optimizing Two-Dimensional Vehicle Loading and Dispatching Decisions in Freight Logistics | Authors: | Yücel, Eda Salman F.S. Erdoğan G. |
Keywords: | Adaptive large neighborhood search Logistics Long-haul freight logistics Mixed integer programming model Vehicle loading and dispatching Decision making Digital storage Fleet operations Freight transportation Integer programming Loading Adaptive large neighborhood searches Dispatching problem Due dates Loading problem Long haul Long-haul freight logistic Mixed integer programming model Two-dimensional Vehicle dispatching Vehicle loading Vehicles |
Publisher: | Elsevier B.V. | Source: | Yücel, E., Salman, F. S., & Erdoğan, G. (2022). Optimizing two-dimensional vehicle loading and dispatching decisions in freight logistics. European Journal of Operational Research, 302(3), 954-969. | Abstract: | This paper introduces a multi-period, two-dimensional vehicle loading and dispatching problem, called Two-Dimensional Vehicle Loading and Dispatching Problem with Incompatibility Constraints (VLDP). The problem concerns preparing a single-origin single-destination transportation plan of loading required orders to vehicles at the origin and dispatching the vehicles to deliver the orders to the destination within their due dates. The decision maker uses their own fleet of vehicles, with each vehicle having a fixed transportation cost per trip, and may outsource additional vehicles at a higher cost. VLDP involves constraints regarding the due dates of the orders, pairwise incompatibility of orders packed in the same vehicle, incompatibility of orders and vehicles, as well as area and weight capacity of the vehicles. An order can be delivered earlier than its due date, incurring an earliness penalty due to storage requirements at the destination. The objective is to minimize the total vehicle usage and earliness penalty costs. A Mixed-Integer Linear Programming model (MILP) is provided, as well as an Adaptive Large Neighbourhood Search (ALNS) algorithm. Results of computational experiments on instances derived from real-world data show the effectiveness of the ALNS algorithm. © 2022 Elsevier B.V. | URI: | https://doi.org/10.1016/j.ejor.2022.01.021 https://hdl.handle.net/20.500.11851/8654 |
ISSN: | 0377-2217 |
Appears in Collections: | Endüstri Mühendisliği Bölümü / Department of Industrial Engineering Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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