scholarly journals Comparison of two hybrid algorithms on incorporated aircraft routing and crew pairing problems

2020 ◽  
Vol 18 (3) ◽  
pp. 1665
Author(s):  
Mohamed N. F. ◽  
Mohamed N. A. ◽  
Mohamed N. H. ◽  
Subani N.
Keyword(s):  
Computational Results ◽  
Airline Operations ◽  
Sequential Method ◽  
Swarm Optimization ◽  
Routing Problem ◽  
Operations Planning ◽  
Aircraft Routing ◽  
Crew Pairing ◽  
Pairing Problem ◽  
Two Hybrid

<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>

scholarly journals Development of Hybrid Algorithm for Integrated Aircraft Routing Problem and Crew Pairing Problem

2017 ◽  
Vol 9 (48) ◽  
Author(s):  
NurulFarihan Mohamed ◽  
ZaitulMarlizawati Zainuddin ◽  
Said Salhi ◽  
Nurul Huda Mohamed ◽  
NurulAkmal Mohamed
Keyword(s):  
Hybrid Algorithm ◽  
Routing Problem ◽  
Aircraft Routing ◽  
Crew Pairing ◽  
Pairing Problem

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
Keyword(s):  
Heuristic Method ◽  
Integrated Model ◽  
Exact Method ◽  
Routing Problem ◽  
Aircraft Routing ◽  
Suboptimal Solutions ◽  
Constructive Heuristic ◽  
Schedule Design ◽  
Crew Pairing ◽  
Pairing Problem

<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>

A matheuristic for the robust integrated airline fleet assignment, aircraft routing, and crew pairing problem

2021 ◽  
pp. 105551
Author(s):  
Mohamed Ben Ahmed ◽  
Maryia Hryhoryeva ◽  
Lars Magnus Hvattum ◽  
Mohamed Haouari
Keyword(s):  
Fleet Assignment ◽  
Aircraft Routing ◽  
Crew Pairing ◽  
Pairing Problem ◽  
Airline Fleet

scholarly journals THE INTEGRATED AIRCRAFT ROUTING AND CREW PAIRING PROBLEM: ILP BASED FORMULATIONS

2016 ◽  
Vol 78 (6-5) ◽  
Author(s):  
Nurul Farihan Mohamed ◽  
Zaitul Marlizawati Zainuddin ◽  
Said Salhi ◽  
Nurul Akmal Mohamed
Keyword(s):  
Solution Method ◽  
Benders Decomposition ◽  
Planning Process ◽  
Minimum Cost ◽  
Problem Model ◽  
Aircraft Routing ◽  
Crew Pairing ◽  
Pairing Problem ◽  
Programming Solution ◽  
Important Objective

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. 

scholarly journals Performance Comparison between Particle Swarm Optimization and Differential Evolution Algorithms for Postman Delivery Routing Problem

2021 ◽  
Vol 11 (6) ◽  
pp. 2703
Author(s):  
Warisa Wisittipanich ◽  
Khamphe Phoungthong ◽  
Chanin Srisuwannapa ◽  
Adirek Baisukhan ◽  
Nuttachat Wisittipanit
Keyword(s):  
Particle Swarm Optimization ◽  
Differential Evolution ◽  
Particle Swarm ◽  
Performance Comparison ◽  
Swarm Optimization ◽  
Routing Problem ◽  
Metaheuristic Methods ◽  
Evolution Algorithms ◽  
Differential Evolution Algorithms ◽  
Current Practices

Generally, transportation costs account for approximately half of the total operation expenses of a logistics firm. Therefore, any effort to optimize the planning of vehicle routing would be substantially beneficial to the company. This study focuses on a postman delivery routing problem of the Chiang Rai post office, located in the Chiang Rai province of Thailand. In this study, two metaheuristic methods—particle swarm optimization (PSO) and differential evolution (DE)—were applied with particular solution representation to find delivery routings with minimum travel distances. The performances of PSO and DE were compared along with those from current practices. The results showed that PSO and DE clearly outperformed the actual routing of the current practices in all the operational days examined. Moreover, DE performances were notably superior to those of PSO.

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