@conference { ISI:000391354500050,
	title = {Feature selection and parameter optimization of support vector regression for electric load forecasting},
	booktitle = {2016 INTERNATIONAL CONFERENCE ON ELECTRICAL AND INFORMATION TECHNOLOGIES (ICEIT)},
	year = {2016},
	note = {2nd International Conference on Electrical and Information Technologies (ICEIT), Tangier, MOROCCO, MAY 04-07, 2016},
	pages = {288-293},
	abstract = {Forecasting of future electricity demand has become a promising issue for the electric power industry. Since many factors affect electric load data, machine learning methods are useful for electric load forecasting (ELF). On the one hand, it is important to determine the irrelevant factors as a preprocessing step for ELF. On the other hand, the performance of machine learning models depends heavily on the choice of its parameters. These problems are known respectively as feature selection and model selection problems. In this paper, we use the support vector regression (SVR) model for ELF. Our contribution consists of investigating the use the particle swarm optimization for both feature selection and model selection problems. Experimental results on two widely used electric load dataset show that our proposed hybrid method for feature selection and parameter optimization of SVR can achieve better results when compared with the classical SVR model while using feature selection and without using it.},
	isbn = {978-1-4673-8469-8},
	author = {Sarhani, Malek and El Afia, Abdellatif},
	editor = {Essaaidi, M and ElHani, S}
}
@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:000392439200033,
	title = {Proposal of a modeling approach and a set of KPI to the drug supply chain within the hospital},
	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 = {The hospital is a complex system where many actors are involved; The challenges that this environment is facing justify the focus on this research subject. The contribution of the paper includes a proposition of a four-level model, that describes the hospital drug supply chain, based on the combination of the Supply Chain Operation Reference (SCOR) and Business Process Modelling Notation (BPMN), and the identification of a set of key performance indicators (KPI) that assess how well the drugs management process within the hospital are effective and efficient and how to improve them.},
	isbn = {978-1-4673-8571-8},
	author = {Mezouar, Houda and El Afia, Abdellatif and Chiheb, Radouane and Ouzayd, Fatima},
	editor = {Alaoui, AE and Benadada, Y and Boukachour, J}
}
@article { ISI:000366991600005,
	title = {Students{\textquoteright} Perceptions Towards Using Web 2.0 Technologies in Education},
	journal = {INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING},
	volume = {10},
	number = {6},
	year = {2015},
	pages = {32-36},
	abstract = {The purpose of this paper is to evaluate the usefulness of Web 2.0 technologies in education. For this purpose, a survey was carried out to explore the students{\textquoteright} perceptions towards using these tools for learning purposes. Results of the research study revealed that all the respondents are greatly immersed in these social platforms and use them for many reasons. However, it was found out that almost half of the surveyed students (i.e. 47\%) devote more than 40\% of the time they spend on Web 2.0 technologies to enhance their learning in different subjects. Taking these findings into consideration, we can stipulate that Web 2.0 applications present many educational advantages for students, hence, contribute in providing opportunities for further learning. Consequently, these online tools provide schools and universities with more opportunities to go beyond traditional delivery formats and develop learnercentered personalized learning environments.},
	issn = {1868-8799},
	doi = {10.3991/ijet.v10i6.4858},
	author = {Faizi, Rdouan and Chiheb, Raddouane and El Afia, Abdellatif}
}
@conference { ISI:000371484600034,
	title = {Application of Multi-Agent Markov Decision Processes to Gate Assignment Problem},
	booktitle = {2014 THIRD IEEE INTERNATIONAL COLLOQUIUM IN INFORMATION SCIENCE AND TECHNOLOGY (CIST{\textquoteright}14)},
	series = {Colloquium in Information Science and Technology},
	year = {2014},
	note = {3rd IEEE International Colloquium on Information Science and Technology (CIST), Tetouan, MOROCCO, OCT 20-22, 2014},
	pages = {196-201},
	publisher = {IEEE; IEEE Comp Soc; IEEE Commun Soc; IEEE Morocco Sect; IEEE Morocco Comp \& Commun Joint Chapter; UAE IEEE Student Branch; Univ Abdelmalek Essaadi; ENSA Tetouan},
	organization = {IEEE; IEEE Comp Soc; IEEE Commun Soc; IEEE Morocco Sect; IEEE Morocco Comp \& Commun Joint Chapter; UAE IEEE Student Branch; Univ Abdelmalek Essaadi; ENSA Tetouan},
	abstract = {Gate assignment Problem (GAP) is an important subject of airport management to ensure smooth traffic operations. However, flights schedule may undergo some stochastic events such as delays that usually occur and have to be considered in the planning. Our approach considers the representation of gates as collaborative agents trying to complete a set of flights assignment tasks as given by a centralized controller. That will allow giving a new model for the GAP based on Multi Agent Markov Decision Processes (MMDP). The aim of this work is to give to controllers at the airport a robust priory solution instead of taking the risk of online schedule modifications to handle uncertainty. The solution of this problem will be a set of optimal decisions to be taken in every case of traffic disturbance.},
	isbn = {978-1-4799-5979-2},
	issn = {2327-185X},
	author = {Aoun, Oussama and El Afia, Abdellatif},
	editor = {ElMohajir, M and AlAchhab, M and Chahhou, M}
}
@conference { ISI:000346582400013,
	title = {An Extension of X13-ARIMA-SEATS to Forecast Islamic Holidays Effect on Logistic Activities},
	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 = {79-84},
	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 = {To better manage and optimize logistic activities, factors that affect it must be determined: The calendar effect is one of these factors which must be analyzed. Analyzing such kind of data by using classical time series forecasting methods, such as exponential smoothing method and ARIMA model, will fail to capture such variation. This paper is released to present a review of the models which are used to forecast the calendar effect, especially moving holidays effect. We adopt the recent approach of X13-ARIMA-SEATS and extend it for being able to forecast the effect of Islamic holidays. Our extension is applied to Moroccan case studies, and aims to give recommendations concerning this effect on logistic activities.},
	isbn = {978-1-4799-4650-1},
	author = {Sarhani, Malek and El Afia, Abdellatif},
	editor = {Benadada, Y}
}
@conference { ISI:000380387700064,
	title = {Intelligent System Based Support Vector Regression For Supply Chain Demand Forecasting},
	booktitle = {2014 SECOND WORLD CONFERENCE ON COMPLEX SYSTEMS (WCCS)},
	year = {2014},
	note = {2014 Second World Conference on Complex Systems (WCCS), Agadir, MOROCCO, NOV 10-12, 2014},
	pages = {79-83},
	publisher = {Ibn Zohr Univ; Moroccan Soc of Complex Syst; IEEE Morocco; Int Acad for Syst and Cybernet Sci IASCYS},
	organization = {Ibn Zohr Univ; Moroccan Soc of Complex Syst; IEEE Morocco; Int Acad for Syst and Cybernet Sci IASCYS},
	abstract = {Supply chain management (SCM) is an emerging field that has commanded attention from different communities. On the one hand, the optimization of supply chain which is an important issue, requires a reliable prediction of future demand. On the other hand, It has been shown that intelligent systems and machine learning techniques are useful for forecasting in several applied domains. In this paper, we introduce the machine learning technique of time series forecasting Support Vector Regression (SVR) which is nowadays frequently used. Furthermore, we use the Particle Swarm Optimization (PSO) algorithm to optimize the SVR parameters. We investigate the accuracy of this approach for supply chain demand forecasting by applying it to a case study.},
	isbn = {978-1-4799-4647-1},
	author = {Sarhani, Malek and El Afia, Abdellatif}
}
@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}
}
@conference { ISI:000380387700063,
	title = {A Robust Crew Pairing based on Multi-Agent Markov Decision Processes},
	booktitle = {2014 SECOND WORLD CONFERENCE ON COMPLEX SYSTEMS (WCCS)},
	year = {2014},
	note = {2014 Second World Conference on Complex Systems (WCCS), Agadir, MOROCCO, NOV 10-12, 2014},
	pages = {762-768},
	publisher = {Ibn Zohr Univ; Moroccan Soc of Complex Syst; IEEE Morocco; Int Acad for Syst and Cybernet Sci IASCYS},
	organization = {Ibn Zohr Univ; Moroccan Soc of Complex Syst; IEEE Morocco; Int Acad for Syst and Cybernet Sci IASCYS},
	abstract = {Airline scheduling is a real challenge in the context of the airline industry; this includes a lot of planning and operational decision problems and deals with a large number of interdependent resources. A prominent problem in airline scheduling is crew scheduling, specially pairings or Tour-of-Duty planning problem. The objective is to ensure optimal allocation of crews to flights by specifying the set of pairings that minimize the planned cost. The widely used algorithms assume no disruptions. However, airline operations often undergo stochastic disturbances that have to be taken into account in order to minimize the real operating cost. Recently, great interest has been given to robust crew scheduling with consideration of the stochastic nature of disturbances like technical breakdowns or bad weather conditions. In this paper, we develop a stochastic model of crew pairing problem based on Multi-agent Markov Decision Processes (MMDP); thus, the problem will be treated as finding the optimal policy to adopt in stochastic cases of disturbances. Also, a computational study is conducted to ensure validity of our proposed model.},
	isbn = {978-1-4799-4647-1},
	author = {Aoun, Oussama and El Afia, Abdellatif}
}
@conference { ISI:000367082904073,
	title = {SOCIAL MEDIA AND EDUCATION: FRIENDS OR FOES?},
	booktitle = {ICERI2014: 7TH INTERNATIONAL CONFERENCE OF EDUCATION, RESEARCH AND INNOVATION},
	series = {ICERI Proceedings},
	year = {2014},
	note = {7th International Conference of Education, Research and Innovation (ICERI), Seville, SPAIN, NOV 17-19, 2014},
	pages = {4410-4414},
	abstract = {Though being relatively a recent addition to the internet landscape, social media have witnessed an exponential growth in the last few years. These are used today in every aspect of our personal and professional lives and are infiltrating nearly every field, including education. In fact, students all over the world are greatly immersed in these web-based applications and have recourse to them to interact with friends, play games and watch television and most importantly to learn. Given the increasing use of these technologies for educational purposes, many educators have started questioning the validity and usefulness of such tools in education, stating that they may distract students and disengage them from learning. The objective of this paper is, therefore, to evaluate the use of these social online platforms in education. To this end, a survey was conducted to examine the perceptions and attitudes of higher education students towards using these tools for learning purposes. Results of the research study revealed that 49\% of the informants devote more than 40\% of the time they spend on social media to enhance their learning experience. Concerning the students{\textquoteright} contributions on these social online platforms, it has been noticed that the great majority of the participants in the survey are active members in these networks as they tend to share learning materials and resources. Taking these findings into account, we may claim that social media applications present many educational advantages for students, hence, contribute in providing opportunities for further learning. As such, they provide educators with an opportunity to go beyond traditional delivery formats and design student-centered customized learning environments.},
	isbn = {978-84-617-2484-0},
	issn = {2340-1095},
	author = {Faizi, Rdouan and El Afia, Abdellatif and Chiheb, Raddouane},
	editor = {Chova, LG and Martinez, AL and Torres, IC}
}
@conference { ISI:000346582400007,
	title = {Using Markov Decision Processes to Solve Stochastic Gate Assignment 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 = {42-47},
	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 = {Airport traffic often undergoes some random disruptions, which have to be considered to ensure operational flight-gate assignments. Inadequate assignment of gates may result in flight delays that happen in airport operations and must be taken into account. Here, we are using the original algorithm, based on Markov decision process (MDP) to solve the gate assignment problem (GAP) under uncertainty; we include stochastic parameters that depend on probabilities to express fluctuations in flight operations. The use of MDP for modeling will provide for airport controllers a robust solution for the GAP that takes in consideration possible flight delays. This paper gives the corresponding model, which includes strict constraints of the GAP and other soft constraints like choice preferences of gates. We give experimental results on a sample of real data to demonstrate the feasibility and efficiency of our approach.},
	isbn = {978-1-4799-4650-1},
	author = {Aoun, Oussama and El Afia, Abdellatif},
	editor = {Benadada, Y}
}
@article {9171244020131001,
	title = {Exploring the Potential Benefits of Using Social Media in Education.},
	journal = {International Journal of Engineering Pedagogy},
	volume = {3},
	number = {4},
	year = {2013},
	pages = {50 - 53},
	abstract = {The objective of this work is to investigate the potential benefits of using social media in education. A thorough examination of a large set of these online tools has revealed that social media have many educational advantages. In fact, it has been found out that these web-based applications can improve communication among students and between teachers and students. Thanks to these technologies, both teachers and students can interact with each other in a matter of seconds. Social media can also be used to promote students{\textquoteright} engagement. Students who often complain of being intimidated or bored in the classroom may feel comfortable to express their creativity and voice their opinion on a social network website. Another finding of this study is that social media applications foster collaboration as they allow students to work together to achieve a common goal. Given these educational benefits, we recommend that these online social tools should be used in learning environments. [ABSTRACT},
	keywords = {Benefits, collaboration, communication, Computer assisted instruction, education, engagement, Internet in education, Online social networks, social media, Social networks, Teaching aids \& devices},
	issn = {21924880},
	url = {http://search.ebscohost.com/login.aspx?direct=true\&db=iih\&AN=91712440\&site=ehost-live},
	author = {Faizi, Rdouan and El Afia, Abdellatif and Chiheb, Raddouane}
}
