Automatic air cargo selection and weight balancing: A mixed integer programming approach

• Published in: Transportation research. Part E, Logistics and transportation review Vol. 65; pp. 70 - 83
• Main Authors: Vancroonenburg, Wim, Verstichel, Jannes, Tavernier, Karel, Vanden Berghe, Greet
• Format: Journal Article
• Language: English
• Published: Exeter Elsevier India Pvt Ltd 01.05.2014; Elsevier Sequoia S.A
• Subjects: Air freight service; Aircraft; Aircraft load planning; Decision making models; Energy consumption; Energy efficiency; Integer programming; Linear programming; Profitability; Studies; Transportation problem (Operations research); Weight and balance; Integer programming; Aircraft load planning; Weight and balance
• ISSN: 1366-5545; 1878-5794
• DOI: 10.1016/j.tre.2013.12.013

•The paper describes cargo selection and weight balancing for freight carriers.•It presents a mixed integer programming model enabling decision support.•A wide range of stability, safety and operational constraints are considered.•The model is validated on a representative set of flights of a commercial carrier.•Testing shows an improvement on both selected cargo value and aircraft balancing. The present contribution introduces a mixed integer linear programming model as a decision support tool for air cargo load planning. The main objective for the model is to find the most profitable selection from a set of cargo to be loaded on an aircraft. The secondary objective is to minimise the deviation between the aircraft’s centre of gravity, and a known target value so as to reduce fuel consumption and improve stability. The model is subject to a large number of constraints that ensure structural integrity and stability of the aircraft, as well as the safety of the cargo and crew. A set of additional constraints guarantees safe and efficient loading and unloading. Experimental results on real-life data show that the model outperforms human expert planners on both objectives, while remaining computationally fast enough for interactive use. This advocates the use of such a decision support model for all air cargo load planning.