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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
Long-haul freight logistics
Mixed integer programming model
Vehicle loading and dispatching
Decision making
Digital storage
Fleet operations
Freight transportation
Integer programming
Adaptive large neighborhood searches
Dispatching problem
Due dates
Loading problem
Long haul
Long-haul freight logistic
Mixed integer programming model
Vehicle dispatching
Vehicle loading
Issue Date: 2022
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.
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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