FLEET ASSIGNMENT OPTIMIZATION AND FLEET USE EVALUATION ON CREW PAIRING WITHOUT SIT TIME

Meskipun penugasan armada dilakukan terlebih dahulu, namun hasil dari evaluasi pelaksanaan crew pairing ataupun crew rostering dapat menjadi masukan untuk penugasan armada berikutnya. Oleh karena itu, hasil studi diharapkan dapat memberikan pengetahuan tentang jenis dan jumlah armada yang digunakan untuk melayani sejumlah penerbangan pada salah satu penelitian crew pairing. Model dalam studi ini bertujuan untuk meminimumkan total biaya yang dikeluarkan oleh maskapai untuk menerbangkan berbagai jenis armada yang melayani semua penerbangan. Penyusunan model, konfirmasi data, verifikasi model, dan uji coba model dilakukan pada bulan September-Desember 2022. Teknik pengumpulan data yaitu dokumentasi. Jenis data yang dianalisis adalah data sekunder, yang dikelompokkan menjadi data yang berhubungan dengan penerbangan, data armada, dan data yang berkaitan dengan biaya yang dikeluarkan oleh maskapai. Penyelesaian masalah basic Fleet Assignment Model dilakukan dengan bantuan software LINGO 19.0. Berdasarkan hasil penelitian, dapat disimpulkan bahwa minimum total biaya untuk melayani 30 penerbangan yang melibatkan Bandar Udara Internasional Soekarno-Hatta, Bandar Udara Internasional I Gusti Ngurah Rai, Bandar Udara Internasional Juanda, dan Bandar Udara Komodo adalah $188,463.1. Jumlah pesawat yang dibutuhkan oleh maskapai untuk melayani semua penerbangan pada 10 Oktober 2022 tersebut yaitu 9 pesawat, yang terdiri dari 3 armada Airbus A330-300 dan 6 armada Boeing 737-800NG. Perlu dilakukan penelitian tentang strategi maskapai dalam menghadapi permasalahan crew pairing yang tidak memiliki sit time di salah satu penerbangan yang dilayani, tetapi harus terbang dengan penerbangan berikutnya menggunakan jenis armada dan pesawat yang berbeda

A Classification and Assessment of Research Streams on Low Cost Modeling in Civil Aviation Transportation Industry

This article attempts to identify key research streams in Civil Aviation Transportation Industry during the past decade and highlights the evolution of the literature. Progress in six established research thrusts and a new research stream is discussed. Using content analysis, the existing research is also examined from a methodological point of view. The review provides evidence for an increasingly sophisticated and rich body of knowledge in global Civil Aviation Transportation Industry. Keywords: Civil Aviation Transportation Industry (CATI), Low Cost Strategies (LCS), Low Cost Carriers (LCCs), Classification, Assessment

Future aircraft networks and schedules

This thesis has focused on an aircraft schedule and network design problem that involves multiple types of aircraft and flight service. First, this thesis expands a business model for integrating on-demand flight services with the traditional scheduled flight services. Then, this thesis proposes a three-step approach to the design of aircraft schedules and networks from scratch. After developing models in the three steps and creating large-scale instances of these models, this dissertation develops iterative algorithms and subproblem approaches to solving these instances, and it presents computational results of these large-scale instances. To validate the models and solution algorithms developed, this thesis compares the daily flight schedules that it designed with the schedules of the existing airlines. In addition, it discusses the implication of using new aircraft in the future flight schedules. Finally, future research in three areas--model, computational method, and simulation for validation--is proposed.Ph.D.Committee Chair: Johnson, Ellis; Committee Co-Chair: Clarke, John-Paul; Committee Member: Ergun, Ozlem; Committee Member: Nemirovski, Arkadi; Committee Member: Smith, Barr

Methods for Improving Robustness and Recovery in Aviation Planning.

In this dissertation, we develop new methods for improving robustness and recovery in aviation planning. In addition to these methods, the contributions of this dissertation include an in-depth analysis of several mathematical modeling approaches and proof of their structural equivalence. Furthermore, we analyze several decomposition approaches, the difference in their complexity and the required computation time to provide insight into selecting the most appropriate formulation for a particular problem structure. To begin, we provide an overview of the airline planning process, including the major components such as schedule planning, fleet assignment and crew planning approaches. Then, in the first part of our research, we use a recursive simulation-based approach to evaluate a flight schedule's overall robustness, i.e. its ability to withstand propagation delays. We then use this analysis as the groundwork for a new approach to improve the robustness of an airline's maintenance plan. Specifically, we improve robustness by allocating maintenance rotations to those aircraft that will most likely benefit from the assignment. To assess the effectiveness of our approach, we introduce a new metric, maintenance reachability, which measures the robustness of the rotations assigned to aircraft. Subsequently, we develop a mathematical programming approach to improve the maintenance reachability of this assignment. In the latter part of this dissertation, we transition from the planning to the recovery phase. On the day-of-operations, disruptions often take place and change aircraft rotations and their respective maintenance assignments. In recovery, we focus on creating feasible plans after such disruptions have occurred. We divide our recovery approach into two phases. In the first phase, we solve the Maintenance Recovery Problem (MRP), a computationally complex, short-term, non-recurrent recovery problem. This research lays the foundation for the second phase, in which we incorporate recurrence, i.e. the property that scheduling one maintenance event has a direct implication on the deadlines for subsequent maintenance events, into the recovery process. We recognize that scheduling the next maintenance event provides implications for all subsequent events, which further increases the problem complexity. We illustrate the effectiveness of our methods under various objective functions and mathematical programming approaches.Ph.D.Industrial & Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91539/1/mlapp_1.pd

Cost/benefit trade-offs for reducing the energy consumption of commercial air transportation (RECAT)

A study has been performed to evaluate the opportunities for reducing the energy requirements of the U.S. domestic air passenger transport system through improved operational techniques, modified in-service aircraft, derivatives of current production models, or new aircraft using either current or advanced technology. Each of the fuel-conserving alternatives has been investigated individually to test its potential for fuel conservation relative to a hypothetical baseline case in which current, in-production aircraft types are assumed to operate, without modification and with current operational techniques, into the future out to the year 2000

Integrating the fleet assignment model with uncertain demand

This thesis was submitted for the degree of Master of Philosophy and awarded by Brunel University.One of the main challenges facing the airline industry is planning under uncertainty, especially in the context of schedule disruptions. The robust models and solution algorithms that have been proposed and developed to handle the uncertain parameters will be discussed. Fleet assignment models (FAM) are used by many airlines to assign aircraft to fights in a schedule to maximize profit. In the context of FAM, the goal of robustness is to produce solutions that perform well relative to uncertainties in demand and operation. In this thesis, we introduce new FAMs (i.e. DFAM1 and DFAM2) that tackles the common problem associated with aircraft utilization. Subsequently, stochastic programming (SP) is presented as a method of choice for the research. Through the use of a two-stage SP with recourse technique, the DFAMs are extended to SP-FAMs (SP-FAM1 and SP-FAM2). The main distinction of the SP-FAM compared with other FAMs is that, given a stochastic passenger demand, it gives a strategic fleet assignment solution that hedges against all possible tactical solutions. In addition, we have a tactical solution for every scenario. In generating the demand scenarios, we use a network-simulation model embedded with a time-series engine that gives a snapshot of one week that is representative of any other week of the scheduling season. We later outline the approach of solving the SP-FAMs where the schedule is compacted through several preprocessing steps before inputting it into SAS-AMPL converter. The SAS-AMPL converter prepares all the data into readable AMPL format. Finally, we execute the optimizer using a FortMP solver (integrated in AMPL) that invokes branch-and-bound algorithm. We give a proof of concept using real data from a Middle East airline. Our investigations establish clear benefits of the recourse FAM compared to alternative models. Finally, we propose areas of future research to improve SP-FAM robustness through solution algorithms, revenue management (RM) effects, calibration of network-simulation models and system integration

Airline fleet assignment and schedule design : integrated models and algorithms

Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2002.Includes bibliographical references (p. 187-192).In scheduled passenger air transportation, airline profitability is critically influenced by the airline's ability to construct flight schedules containing flights at desirable times in profitable markets. In this dissertation, we study two elements of the schedule generation process, namely, schedule design and fleet assignment. The schedule design problem involves selecting an optimal set of flight legs to be included in the schedule, while the fleet assignment problem involves assigning aircraft types (or fleets) to flight legs to maximize revenues and minimize operating costs simultaneously. With the fleet assignment problem, we investigate the issues of network effects, spill, and recapture. On a constrained flight leg in which demand exceeds capacity, some passengers are not accommodated, or spilled. When passengers travel on two or more constrained legs, flight leg interdependencies or network effects arise because spill can occur on any of these legs. In most basic fleet assignment models, simplistic modeling of network effects and recapture leads to sometimes severe, miscalculations of revenues. Recapture occurs when some of the spilled passengers are re-accommodated on alternate itineraries in the system. In this dissertation, we develop new fleet assignment models that capture network effects, spill, and recapture. Another benefit of one of our models is its tractability and potential for further integration with other schedule planning steps.(cont.) Our study shows that the benefits of modeling these elements can be as large as $100 million annually for a major U.S. airline. In addition, we show that modeling flight leg interdependence is more important than demand stochasticity for hub-and-spoke fleet assignment problems. We develop two models for schedule design, one assuming that the market share of an airline remains constant with schedule changes; and the other assuming that market share varies with schedule changes. The constant market share model, while less precise in its modeling, is much easier to solve than the variable market share model. We estimate that the potential benefits of these models range from$100 to $350 million annually.Manoj Lohatepanont.Sc.D