A Heuristic and Exact Method: Integrated Aircraft Routing and Crew Pairing Problem

2016 ◽  
Vol 10 (4) ◽  
pp. 128 ◽  
Author(s):  
Nurul Farihan Mohamed ◽  
Zaitul Marlizawati Zainuddin ◽  
Said Salhi ◽  
Nurul Huda Mohamed ◽  
Nurul Akmal Mohamed

<p>In airline operations planning, there are four problems which are schedule design, fleet assignment, aircraft routing and crew pairing problem. Those problems are sequentially and interdependent. Aircraft routing and crew pairing problem are hard to solve and normally crew pairing problem dependent to the aircraft routing problem which gives the suboptimal solutions. As minimizing the costs is important in the airline system, so in order to tackle suboptimal solutions, aircraft routing problem and crew pairing problem are being integrated in one model. For solving the integrated model, the feasible aircraft routes and crew pairs are required. Because of that, a method is being proposed in this work for generating the feasible aircraft routes and crew pairs which is the constructive heuristic method. By using the generic aircraft routes and crew pairs, the integrated model then being solve by two approaches. The first approach is the exact method called the integer linear programming (ILP) while the second approach is from the heuristic method called particle swarm optimization. Encouraging results are encountered by testing on four types of aircrafts for one week flight cycle from local flights in Malaysia.</p>

Author(s):  
NurulFarihan Mohamed ◽  
ZaitulMarlizawati Zainuddin ◽  
Said Salhi ◽  
Nurul Huda Mohamed ◽  
NurulAkmal Mohamed

Author(s):  
Mohamed N. F. ◽  
Mohamed N. A. ◽  
Mohamed N. H. ◽  
Subani N.

<span>In airline operations planning, a sequential method is traditionally used in airline system. In airline systems, minimizing the costs is important as they want to get the highest profits. The aircraft routing problem is solved first, and then pursued by crew pairing problem. The solutions are suboptimal in some cases, so we incorporate aircraft routing and crew pairing problems into one mathematical model to get an exact solution. Before we solve the integrated aircraft routing and crew pairing problem, we need to get the aircraft routes (AR) and crew pairs (CP). In this study, we suggested using genetic algorithm (GA) to develop a set of AR and CP. By using the generated AR and CP, we tackle the integrated aircraft and crew pairing problems using two suggested techniques, Integer Linear Programming (ILP) and Particle Swarm Optimization (PSO). Computational results show that GA's executed of AR and CP and then solved by ILP obtained the greatest results among all the methods suggested.</span>


2021 ◽  
pp. 105551
Author(s):  
Mohamed Ben Ahmed ◽  
Maryia Hryhoryeva ◽  
Lars Magnus Hvattum ◽  
Mohamed Haouari

2016 ◽  
Vol 78 (6-5) ◽  
Author(s):  
Nurul Farihan Mohamed ◽  
Zaitul Marlizawati Zainuddin ◽  
Said Salhi ◽  
Nurul Akmal Mohamed

Minimization of cost is very important in airline as great profit is an important objective for any airline system. One way to minimize the costs in airline is by developing an integrated planning process. Airline planning consists of many difficult operational decision problems including aircraft routing and crew pairing problems. These two sub-problems, though interrelated in practice, are usually solved sequentially leading to suboptimal solutions. We propose an integrated aircraft routing and crew pairing problem model, one approach to generate the feasible aircraft routes and crew pairs, followed by three approaches to solve the integrated model. The integrated aircraft routing and crew scheduling problem is to determine a minimum cost aircraft routes and crew schedules while each flight leg is covered by one aircraft and one crew. The first approach is an integer programming solution method, the second formulation is developed in a way to lend itself to be used efficiently by Dantzig Wolfe decomposition whereas the third one is formulated as a Benders decomposition method. Encouraging results are obtained when tested on four types of aircraft based on local flights in Malaysia for one week flight cycle. 


Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3327
Author(s):  
Vildan Özkır ◽  
Mahmud Sami Özgür

High profitability and high costs have stiffened competition in the airline industry. The main purpose of the study is to propose a computationally efficient algorithm for integrated fleet assignments and aircraft routing problems for a real-case hub and spoke airline planning problem. The economic concerns of airline operations have led to the need for minimising costs and increasing the ability to meet rising demands. Since fleets are the most limited and valuable assets of airline carriers, the allocation of aircraft to scheduled flights directly affects profitability/market share. The airline fleet assignment problem (AFAP) addresses the assignment of aircraft, each with a different capacity, capability, availability, and requirement, to a given flight schedule. This study proposes a mathematical model and heuristic method for solving a real-life airline fleet assignment and aircraft routing problem. We generate a set of problem instances based on real data and conduct a computational experiment to assess the performance of the proposed algorithm. The numerical study and experimental results indicate that the heuristic algorithm provides optimal solutions for the integrated fleet assignment and aircraft routing problem. Furthermore, a computational study reveals that compared with the heuristic method, solving the mathematical model takes significantly longer to execute.


Author(s):  
S.P. Wilson ◽  
M.C. Bartholomew-Biggs ◽  
S.C. Parkhurst

This chapter describes the formulation and solution of a multi-aircraft routing problem which is posed as a global optimization calculation. The chapter extends previous work (involving a single aircraft using two dimensions) which established that the algorithm DIRECT is a suitable solution technique. The present work considers a number of ways of dealing with multiple routes using different problem decompositions. A further enhancement is the introduction of altitude to the problems so that full threedimensional routes can be produced. Illustrative numerical results are presented involving up to three aircraft and including examples which feature routes over real-life terrain data.


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