A Mathematical Programming Approach to Airline Crew Pairing Optimization (original) (raw)
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Airline crew scheduling from planning to operations
European Journal of Operational Research, 2007
Crew scheduling problems at the planning level are typically solved in two steps: first, creating working patterns, and then assigning these to individual crew. The first step is solved with a set covering model, and the second with a set-partitioning model. At the operational level, the (re) planning period is considerably smaller than during the strategic planning phase. We integrate both models to solve time critical crew recovery problems arising on the day of operations. We describe how pairing construction and pairing assignment are done in a single step, and provide solution techniques based on simple tree search and more sophisticated column generation and shortest-path algorithms.
A novel column generation strategy for large scale airline crew pairing problems
Expert Systems With Applications, 2016
A crew pairing is a sequence of flight legs beginning and ending at the same crew domicile. Crew pairing planning is the primary cost-determining phase in airline crew scheduling. Optimizing crew pairings of an airline timetable is an extremely important process which helps to minimize operational crew costs and to maximize crew utilization. There are various restrictions imposed by regulations or company policies that must be considered and satisfied in crew pairing generation process. Keeping these restrictions and regulations in mind, the main goal of the optimization is the generation of low cost sets of valid crew pairings which cover all flights in airline's timetable. For this research study, already existing works related to crew pairing optimization are examined and a new column generation strategy, a pricing network design and a pairing elimination heuristic are developed as a contribution to the previous studies. In the proposed strategy, the main problem is modeled and solved as a set-covering problem and the pricing sub problem is modeled as a shortest-path problem which is efficiently solved over a duty-flight overnight connection graph by the combined usage of heuristic and exact algorithms. The proposed strategy has been tested with real world data obtained from Turkish Airlines and it is seen that it is capable of generating very competitive solutions compared to current practices in Turkish Airlines. It is also observed that there are various advantages of proposed solution approach such as sensitivity to penalty coefficients, generating less deadheads, very close solution times with a single threaded software and light weight hardware.
An integer programming approach to generating airline crew pairings
Computers & Operations Research, 2009
The ability to generate crew pairings quickly is essential to solving the airline crew scheduling problem. Although techniques for doing so are well-established, they are also highly customized and require significant implementation efforts. This greatly impedes researchers studying important problems such as robust planning, integrated planning, and automated recovery, all of which also require the generating of crew pairings. As an alternative, we present an integer programming (IP) approach to generating crew pairings, which can be solved via traditional methods such as branch-and-bound using off-the-shelf commercial solvers. This greatly facilitates the prototyping and testing of new research ideas. In addition, we suggest that our modeling approach, which uses both connection variables and marker variables to capture the non-linear cost function and constraints of the crew scheduling problem, can be applicable in other scheduling contexts as well. Computational results using data from a major U.S. hub-and-spoke carrier demonstrate the performance of our approach.
Airline Crew Scheduling: A New Formulation and Decomposition Algorithm
Operations Research, 1997
Airline crew scheduling is concerned with nding a minimum cost assignment of ight crews to a given ight schedule while satisfying restrictions dictated by collective bargaining agreements and the Federal Aviation Administration. Traditionally, the problem has been modeled as a set partitioning problem. In this paper, we present a new model based on breaking the decision process into two stages. In the rst stage we select a set of duty periods that cover the ights in the schedule. Then, in the second stage, we attempt to build pairings using those duty periods. We suggest a decomposition approach for solving the model and present computational results for test problems provided by a major carrier. Our formulation provides a tighter linear programming bound than that of the conventional set partitioning formulation but is more di cult to solve.
A heuristic method for solving airline crew pairing problems
MATEC Web of Conferences, 2018
The airline crew pairing problem is one of the optimization problems which classified as a NP-hard problem. Since the number of feasible pairings in flight schedules can be numerous, the exact methods will not efficient to solve the problem. We propose a heuristic method for solving crew pairing problems. Initially, we generate a feasible solution by maximizing the covered flights. Then, we improve the solution by constructing a procedure to avoid the local optimal solution. We test our method to an airline schedules. The computational results show that our method can give the optimal solution in short period of time.
Operations Research in Crew Scheduling for Airlines
2019
Airline Crew Scheduling is an important part of airline operations and an interesting problem for application of operations research. The objective is to assign crew at minimum cost on the basis of given constraints using personalized rosters or bidlines. We have given a far reaching depiction of aircraft crew scheduling issues and numerical models used to solve the different constraints and objectives. We present solution methodologies by integer programming method that has been used to solve crew pairing problem and crew rostering problems.
Heuristics to solve the integrated airline crew assignment problem
Journal of Transport Literature, 2015
Keywords: air transportation airline crew assignment combinatorial optimization heuristics A typical problem related to airline crew management consists of optimally assigning the required crew members to planned flights for a given period of time, while complying with a variety of labor regulations, safety rules and policies of the airline. This problem, called crew assignment problem (CAP), is of the NP-Hard class. So, it is usually divided into two independent subproblems, crew pairing problem (CPP) and crew rostering problem (CRP), modeled and solved sequentially. This division does not provide a global treatment to the CAP in terms of total cost and quality of the final solution. The state of the art involves the integrated solution of CAP, with both subproblems (CPP and CRP) solved simultaneously. It still requires high computational effort. Its combinatorial nature makes it difficult (or even impossible) to be solved by exact methods. The methodology proposed in this research provides an integrated solution of the CAP with heuristic procedures. The methodology was tested to solve instances related to small and medium-sized Brazilian airlines. The results were also compared with those obtained through an exact model adapted from the literature.
arXiv: Mathematical Software, 2020
Crew Pairing Optimization aims at generating a set of flight sequences (crew pairings), covering all flights in an airline's flight schedule, at minimum cost, while satisfying several legality constraints. CPO is critically important for airlines' business viability, considering that the crew operating cost is their second-largest expense. It poses an NP-hard combinatorial optimization problem, to tackle which, the state-of-the-art relies on relaxing the underlying Integer Programming Problem (IPP) into a Linear Programming Problem (LPP), solving the latter through Column Generation (CG) technique, and integerization of the resulting LPP solution. However, with the growing scale and complexity of the flight networks (those with a large number of flights, multiple crew bases and/or multiple hub-and-spoke subnetworks), the utility of the conventional CG-practices has become questionable. This paper proposed an Airline Crew Pairing Optimization Framework, AirCROP, whose constit...
ArXiv, 2020
For an airline, the crew operating cost is second only to the fuel cost, making the crew pairing optimization (CPO) critical for business viability. Its aim is to generate a set of flight sequences (crew pairings) that cover all flights in an airline's schedule, at minimum cost, while satisfying several legality constraints. Being an NP-hard combinatorial optimization problem, CPO is tackled by relaxing the underlying Integer Programming Problem into a Linear Programming Problem, and solving the latter through Column generation (CG) technique. However, with the expansion of airlines' operations lately, the curse of dimensionality renders the exact CG-implementations obsolete, paving the way for heuristic-based CG-implementations. Yet, the much prevalent large-scale complex flight networks involving multiple-crew bases and hub-and-spoke sub-networks, largely remain unaddressed. To bridge the research gap, this paper proposes a novel CG heuristic, which has enabled in-house de...