Revenue management of air cargo service in theory and practice

Budiarto, Sony Panca; Putro, Heru Purboyo Hidayat; Pradono, Pradono; Yudoko, Gatot

doi:10.1088/1755-1315/158/1/012022

Cited by 7 publications

(5 citation statements)

References 33 publications

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“…At present, research on aviation logistics includes ground distribution path planning, freight forwarding, airport management, etc. [15], but research on loading optimization is relatively few.…”

Section: Discussionmentioning

confidence: 99%

Research on Airfreight Loading Optimization of E-Commerce Logistics Based on Improved Genetic Algorithm

2021

IJOMAM

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At present, more and more e-commerce logistics use airfreight. To further optimize the freight loading problem, this study first established the freight loading optimization model, improved the genetic algorithm to solve the model, and made an example analysis. It was found that the load utilization rate was 96.63%, and the space utilization rate was 92.95% in the scheme obtained by the algorithm proposed in this study, which was higher than those of the other two algorithms. In the aspect of calculation time, the method proposed in this study could obtain the optimal scheme in 56.78 s. The experimental results show that the proposed algorithm performs better in the loading optimization problem and can be further promoted and applied.

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Section: Discussionmentioning

confidence: 99%

Research on Airfreight Loading Optimization of E-Commerce Logistics Based on Improved Genetic Algorithm

2021

IJOMAM

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“…-Necessary documents such as products, airline invoice and sender's certificate are examined. The products are loaded into the trunk of the aircraft by creating a unit load (ULD) [16].…”

Section: Business Nature Of Air Cargo and Recent Developmentsmentioning

confidence: 99%

Bibliometric Analysis on Air Cargo Transportation for Two Decades

Yıldız

Taşdemir²

2021

Journal of Aviation

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This study examines the scientific studies on Air Cargo via bibliometric analysis for two decades. The aim of study is determining the intellectual structure of the air cargo focused studies, reveal its evolutionary development in the area and identify the research gaps or topics for further studies may be needed. Dimensions database was used to obtain bibliometric data. "Air Cargo" OR "Air Freight" AND "Supply Chain Management" keyword combination was selected to define the primary focused area. "Commerce, Management and Tourism" or "Transportation and Freight Services" or "Business and Management" sub-categories defined as research content. 492 journal articles were analysed with bibliometric techniques and WosViewer software used for visualization. Analysis indicates that most of citied and majority of published articles had found place on interdisciplinary researches. Studies which are linked to production, management and international supply chain operations got more attention compared to focused solely on air cargo ones. Besides, USA, UK and China were determined as most productive countries and Cranfield University was ranked first among institutions. According to another result, two main clusters were also observed in collaborations between universities/institutions as Eastern and Western settled. International Journal of Physical Distribution and Logistics Management was determined the leader of journals. Only journal which focused solely aviation research is Journal of Air Transport Management. With rising trend and new developments in both aviation and supply chain management are foreseen that researches in the area will sustain its rising trend in the future. Especially environmental, e-trade, labour and other interdisciplinary issues will need to be examined deeply.

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“…The first research overview of issues surrounding air cargo revenue management were introduced in [11]. Since then the research literature has seen a steady growth with works including [5,16]. Our work closely follows the decision making paradigm introduced by [1] for modeling both volume and weight aspects of bookings in air-cargo RM.…”

Section: Related Workmentioning

confidence: 99%

“…We have overloaded the f θ signature to emphasize the role of bkvol5 It is S (T , m), Stirling number of second kind…”

mentioning

confidence: 99%

AI-CARGO: A Data-Driven Air-Cargo Revenue Management System

Rizzo,

Lucas,

Kaoudi

et al. 2019

Preprint

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We propose AI-CARGO, a revenue management system for aircargo that combines machine learning prediction with decisionmaking using mathematical optimization methods. AI-CARGO addresses a problem that is unique to the air-cargo business, namely the wide discrepancy between the quantity (weight or volume) that a shipper will book and the actual received amount at departure time by the airline. The discrepancy results in sub-optimal and inefficient behavior by both the shipper and the airline resulting in overall loss of potential revenue for the airline. AI-CARGO also includes a data cleaning component to deal with the heterogeneous forms in which booking data is transmitted to the airline cargo system. AI-CARGO is deployed in the production environment of a large commercial airline company. We have validated the benefits of AI-CARGO using real and synthetic datasets. Especially, we have carried out simulations using dynamic programming techniques to elicit the impact on offloading costs and revenue generation of our proposed system. Our results suggest that combining prediction within a decision-making framework can help dramatically to reduce offloading costs and optimize revenue generation.

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Revenue management of air cargo service in theory and practice

Cited by 7 publications

References 33 publications

Research on Airfreight Loading Optimization of E-Commerce Logistics Based on Improved Genetic Algorithm

Research on Airfreight Loading Optimization of E-Commerce Logistics Based on Improved Genetic Algorithm

Bibliometric Analysis on Air Cargo Transportation for Two Decades

AI-CARGO: A Data-Driven Air-Cargo Revenue Management System

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