Aircraft replacement scheduling: A dynamic programming approach

Hsu, Chaug‐Ing; Li, Hui-Chieh; Liu, Su-Miao; Chao, Ching-Cheng

doi:10.1016/j.tre.2010.07.006

Cited by 44 publications

(22 citation statements)

References 16 publications

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“…In this study, an implementation for a Model driven presented in [1] is given aiming to help EGYPTAIR airline to make decisions regarding purchasing, leasing and disposing of their aircraft over a period of time which will construct the decision based on fleet cost function and the stochastic dynamic programming model mentioned before in sections (2.2) and (2.1) respectively. Our implemented DSS is designed as the following phases:-Data collection phase All required data are collected for fleet capacity, aircrafts in the fleet and routes carried by the airline such as:--Aircraft type, age, mileage traveled and number of seats.…”

Section: Decision Support Systemmentioning

confidence: 99%

“…There are a few literature available on replacement cost in relation to fleet capacity management over different periods, or for revenue loss associated with dynamic and cyclical demand. On the other hand Hsu et al in [1] developed a stochastic dynamic programming model to optimize airline decisions that related to purchasing, leasing, or disposing of aircraft over time based on dynamic programming model. In this work an implementation for the model presented in [1] is applied to EGYPTAIR Airlines fleet capacity management to automatically schedule Decisions regarding purchasing, leasing or disposing of aircraft over a period of time.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand Hsu et al in [1] developed a stochastic dynamic programming model to optimize airline decisions that related to purchasing, leasing, or disposing of aircraft over time based on dynamic programming model. In this work an implementation for the model presented in [1] is applied to EGYPTAIR Airlines fleet capacity management to automatically schedule Decisions regarding purchasing, leasing or disposing of aircraft over a period of time. This study will discuss the different types of DSS, stochastic dynamic programming model to optimize airline decisions to get the optimal match between fleet capacity and passenger traffic by considering demand fluctuations.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Decision Support System for Airlines Fleet Capacity Management

El-Din¹,

Ghali²,

Sadek³

et al. 2015

IJCA

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Section: Decision Support Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Decision Support System for Airlines Fleet Capacity Management

El-Din¹,

Ghali²,

Sadek³

et al. 2015

IJCA

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“…There exists a variety of methods for describing aircraft replacement strategies. A fairly extensive method is described by Hsu et al (2011) and is applied to Taiwan Airlines. It should be noted that there are differences between the civilian and the military cases.…”

Section: Pbsp Managementmentioning

confidence: 99%

Part-out-based spares provisioning management

Block

Ahmadi²,

Tyrberg³

et al. 2014

Journal of Quality in Maintenance Engineering

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Purpose -The purpose of this paper is to present the prerequisites for a part-out-based spares provisioning (PBSP) programme during the phase-out of an aircraft fleet. Furthermore, associated key decision criteria are identified and a framework for the phase-out management process is presented. Design/methodology/approach -Once a decision has been taken to phase-out an aircraft fleet, a number of routines for operations, maintenance and storage are affected and new tasks and functions must be introduced before initiating the actual parting-out process. A decision-making system and a management framework is needed to manage spares planning during the end-of-life phase to ensure availability at minimum cost and to ensure a manageable risk of backorders. Findings -For PBSP programme during the phase-out of an aircraft fleet to succeed and be cost-effective, a number of linked processes, tasks and decisions are required, e.g., those included in the framework proposed in this paper (see Figure 3). A successful implementation of PBSP also requires that these processes and tasks are carried out in a timely manner and that the communications between the concerned parties are prompt, clear and direct. One experience from the studied case is that close and trustful contacts and cooperation between the operator and maintenance provider(s) will greatly facilitate the process. Originality/value -Although the PBSP method is fairly commonly applied within both the military and the civilian sector, somewhat surprisingly very literature has been published on the subject. Indeed, remarkably little has been published on any aspects of maintenance during the end-of-life period.

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“…In other words, there is a close relationship between the type of aircraft, aircraft quantity, travel demand of passengers, and the service frequency in fleet planning. Past research had shown that if travel demand is estimated stochastically to account for uncertainty, the optimal solutions are more accurate and reliable [6,9,10]. In addition, fleet planning has an added advantage if the demand of varying classes of passengers (i.e., business and economy) is considered [11,12].…”

Section: Introductionmentioning

confidence: 99%

Fleet Planning Decision-Making: Two-Stage Optimization with Slot Purchase

Teoh

Khoo²

2016

Journal of Optimization

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Essentially, strategic fleet planning is vital for airlines to yield a higher profit margin while providing a desired service frequency to meet stochastic demand. In contrast to most studies that did not consider slot purchase which would affect the service frequency determination of airlines, this paper proposes a novel approach to solve the fleet planning problem subject to various operational constraints. A two-stage fleet planning model is formulated in which the first stage selects the individual operating route that requires slot purchase for network expansions while the second stage, in the form of probabilistic dynamic programming model, determines the quantity and type of aircraft (with the corresponding service frequency) to meet the demand profitably. By analyzing an illustrative case study (with 38 international routes), the results show that the incorporation of slot purchase in fleet planning is beneficial to airlines in achieving economic and social sustainability. The developed model is practically viable for airlines not only to provide a better service quality (via a higher service frequency) to meet more demand but also to obtain a higher revenue and profit margin, by making an optimal slot purchase and fleet planning decision throughout the long-term planning horizon.

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Aircraft replacement scheduling: A dynamic programming approach

Cited by 44 publications

References 16 publications

Decision Support System for Airlines Fleet Capacity Management

Decision Support System for Airlines Fleet Capacity Management

Part-out-based spares provisioning management

Fleet Planning Decision-Making: Two-Stage Optimization with Slot Purchase

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