Optimization Applications in the Airline Industry

Yu, Gang; Yang, Jian

doi:10.1007/978-1-4613-0303-9_23

Cited by 15 publications

(9 citation statements)

References 118 publications

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“…The ideal model would provide more cost-effective routing and improve overall network utilization by incorporating the aircraft-and-truck network. Yu and Yang (1998) listed the literature on airline planning, modeling, and optimization. In general, airline planning consists of solving five individual problems: schedule development (determining when and where to fly), fleet assignment (assigning the aircraft equipment types), aircraft routing (assigning aircraft to routes), crew scheduling (determining the crew itineraries or pairings), and crew rostering (assigning crews to crew itineraries).…”

Section: Optimizing Routing Of the Integrated Aircraft-and-trucking Nmentioning

confidence: 99%

Menlo Worldwide Forwarding Optimizes Its Network Routing

Prior¹,

Slavens²,

Trimarco³

et al. 2004

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Since 2000, Menlo Worldwide Forwarding (formerly Emery Worldwide) has faced a particularly challenging business environment that has been exacerbated by a weakened economy, the events of September 11, and a decreasing demand for airfreight. To meet these challenges, the company and Menlo Worldwide Technologies developed a network-routing-optimization model to optimize Menlo Worldwide Forwarding$s North American transportation network. The project team and senior managers have repeatedly identified and applied low cost solutions to meet the changing and complex network-routing requirements. By maximizing its use of network capacity, the company has increased profitability and reduced operating costs while maintaining high service levels. In 2002 alone, Menlo Worldwide Forwarding reduced operating costs by 21 percent, increased operating margin by 41 percent, and improved financial results by $80 million in the North American aircraft transportation operation. Moreover, management used the optimization model to facilitate Menlo$s transition from a heavily asset-based, integrated airfreight company to an asset-light, freight-forwarding business. This created a flexible operating environment and a competitive advantage for future operations.

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Section: Optimizing Routing Of the Integrated Aircraft-and-trucking Nmentioning

confidence: 99%

Menlo Worldwide Forwarding Optimizes Its Network Routing

Prior¹,

Slavens²,

Trimarco³

et al. 2004

Interfaces

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show abstract

“…There have also been models dealing with aircraft reassignment (Jarrah et al [18], Teodorovic and Guberinic [28], and Teodorovic and Stojkovic [29]) and crew recoveries (Arguello, Bard, and Yu [6]) under disruptions, papers specifically studying DM under ground delay programs imposed by the FAA (Andreatta and Romanin-Jacur [5], Luo and Yu [21], and Vranas, Bertsimas, and Odoni [31]), and reviews on the advancement of the DM research in the airline industry (Yu [35] and Yu and Yang [36]). The complexity of the problems forced people to develop special-purpose heuristic algorithms.…”

Section: A Literature Reviewmentioning

confidence: 99%

Disruption management in production planning

Yang

2005

Naval Research Logistics

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Abstract:We study the problem of recovering a production plan after a disruption, where the disruption may be caused by incidents such as power failure, market change, machine breakdown, supply shortage, worker no-show, and others. The new recovery plan we seek after has to not only suit the changed environment brought about by the disruption, but also be close to the initial plan so as not to cause too much customer unsatisfaction or inconvenience for current-stage and downstream operations. For the general-cost case, we propose a dynamic programming method for the problem. For the convex-cost case, a general problem which involves both cost and demand disruptions can be solved by considering the cost disruption first and then the demand disruption. We find that a pure demand disruption is easy to handle; and for a pure cost disruption, we propose a greedy method which is provably efficient. Our computational studies also reveal insights that will be helpful to managing disruptions in production planning.

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“…The fleet assignment problem (FAP), on the other hand, has been extensively studied by researchers and practitioners (see Gopalan and Talluri 1998;Yu and Yang 1998;Zhu 2001 for extensive reviews). Most researchers have used the "daily model" (i.e., the same fleet assignments are used every day of the planning period) for the FAP.…”

Section: Introductionmentioning

confidence: 99%

Polyhedral Analysis and Algorithms for a Demand-Driven Refleeting Model for Aircraft Assignment

Sherali

Bish

Zhu

2005

Transportation Science

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xzhu@vt.edu} T he current airline practice in conducting fleet assignments is to begin assigning aircraft capacity to scheduled flights well in advance of departures. However, the accuracy of the passenger demand forecast improves markedly over time, and revisions to the initial fleet assignment become naturally pertinent when the observed demand differs considerably from the assigned aircraft capacities. The demand-driven refleeting (DDR) approach proposed in this paper offers a dynamic reassignment of aircraft capacities to the flight network, when improved demand forecasts become available, so as to maximize the total revenue. Because of the need to preserve the initial crew schedule, this reassignment approach is limited within a single family of aircraft types and to the flights assigned to this particular family. This restriction makes it computationally tractable to include more relevant path-level demand information into the DDR model. Accordingly, we construct a mixedinteger programming model for this enhanced problem context and study its polyhedral structure to explore ways for tightening its representation and for deriving certain classes of valid inequalities. Various schemes for implementing such reformulation techniques are investigated and tested using a set of simulated and real instances obtained from United Airlines.

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Optimization Applications in the Airline Industry

Cited by 15 publications

References 118 publications

Menlo Worldwide Forwarding Optimizes Its Network Routing

Menlo Worldwide Forwarding Optimizes Its Network Routing

Disruption management in production planning

Polyhedral Analysis and Algorithms for a Demand-Driven Refleeting Model for Aircraft Assignment

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