@conference { ISI:000392439200025,
	title = {Particle swarm optimization with a mutation operator for solving the preventive aircraft maintenance routing problem},
	booktitle = {PROCEEDINGS OF THE 3RD IEEE INTERNATIONAL CONFERENCE ON LOGISTICS OPERATIONS MANAGEMENT (GOL{\textquoteright}16)},
	year = {2016},
	note = {3rd IEEE International Conference on Logistics Operations Management (GOL), Fes, MOROCCO, MAY 23-25, 2016},
	publisher = {Sidi Mohammed Ben Abdellah Univ Fes, Fac Sci \& Technol; Mohammed V Univ Rabat, ENSIAS Sch; Univ Havre; IEEE},
	organization = {Sidi Mohammed Ben Abdellah Univ Fes, Fac Sci \& Technol; Mohammed V Univ Rabat, ENSIAS Sch; Univ Havre; IEEE},
	abstract = {Aircraft Maintenance Routing (AMR) is one of the major optimization problems in the airline industry. In this study, we present a mathematical formulation for the daily AMR problem which aims to minimize the risk of both scheduled and non-scheduled maintenance costs. Exact methods may fail to deal with such problems. Our contribution is then to examine the use of an improved particle swarm optimization (PSO) algorithm by a uniform mutation operator for solving this probabilistic problem. Computational results show that our hybrid approach gives competitive results comparing to the native binary PSO.},
	isbn = {978-1-4673-8571-8},
	author = {Sarhani, Malek and Ezzinbi, Omar and El Afia, Abdellatif and Benadada, Youssef},
	editor = {Alaoui, AE and Benadada, Y and Boukachour, J}
}
@conference { ISI:000346582400008,
	title = {A metaheuristic approach for solving the airline maintenance routing with aircraft on ground problem},
	booktitle = {PROCEEDINGS OF 2014 2ND IEEE INTERNATIONAL CONFERENCE ON LOGISTICS AND OPERATIONS MANAGEMENT (GOL 2014)},
	year = {2014},
	note = {2nd IEEE International Conference on Logistics Operations Management (GOL), Rabat, MOROCCO, JUN 05-07, 2014},
	pages = {48+},
	publisher = {IEEE; Mohammed VI Souissi Univ, ENSIAS Sch; Univ Le Havre; Sidi Mohamed Ben Abdellah Univ, FST},
	organization = {IEEE; Mohammed VI Souissi Univ, ENSIAS Sch; Univ Le Havre; Sidi Mohamed Ben Abdellah Univ, FST},
	abstract = {In the airline industry, the Aircraft Maintenance Routing (AMR) problem has been one of the great successes of operations research. The AMR problem is to determine a particular route for each aircraft to undergo different levels of maintenance checks. The objective is to minimize the total maintenance costs. In this study, our aim is to present a mathematical formulation for the AMR problem which takes into account the case of Aircraft On Ground (AOG). We develop solution approaches based on Particle Swarm Optimization algorithm and Genetic algorithm for solving the problem. The results show the effectiveness of this solution in reducing computational time.},
	isbn = {978-1-4799-4650-1},
	author = {Ezzinbi, Omar and Sarhani, Malek and El Afia, Abdellatif and Benadada, Youssef},
	editor = {Benadada, Y}
}
@conference { ISI:000346582400009,
	title = {Particle swarm optimization algorithm for solving airline crew scheduling problem},
	booktitle = {PROCEEDINGS OF 2014 2ND IEEE INTERNATIONAL CONFERENCE ON LOGISTICS AND OPERATIONS MANAGEMENT (GOL 2014)},
	year = {2014},
	note = {2nd IEEE International Conference on Logistics Operations Management (GOL), Rabat, MOROCCO, JUN 05-07, 2014},
	pages = {52-56},
	publisher = {IEEE; Mohammed VI Souissi Univ, ENSIAS Sch; Univ Le Havre; Sidi Mohamed Ben Abdellah Univ, FST},
	organization = {IEEE; Mohammed VI Souissi Univ, ENSIAS Sch; Univ Le Havre; Sidi Mohamed Ben Abdellah Univ, FST},
	abstract = {In air transport, the cost related to crew members presents one of the most important cost supported by airline companies. The objective of the crew scheduling problem is to determine a minimum-cost set of pairings so that every flight leg is assigned a qualified crew and every pairing satisfies the set of applicable work rules. In this paper, we propose a solution for the crew scheduling problem with Particle Swarm Optimization (PSO) algorithm, this solution approach is compared with the Genetic Algorithm (GA) for both crew pairing and crew assignment problems which are the two part of crew scheduling problem.},
	isbn = {978-1-4799-4650-1},
	author = {Ezzinbi, Omar and Sarhani, Malek and El Afia, Abdellatif and Benadada, Youssef},
	editor = {Benadada, Y}
}
