@article {Lhazmir2020,
	title = {A decision-making analysis in UAV-enabled wireless power transfer for IoT networks},
	journal = {Simulation Modelling Practice and Theory},
	volume = {103},
	year = {2020},
	note = {cited By 8},
	abstract = {We consider an IoT network with energy-harvesting capabilities. To extend the network lifetime, we propose a novel unmanned aerial vehicle (UAV)- enabled wireless power transfer (WPT) system, where UAVs move among IoT devices and act as data aggregators and wireless power providers. This paper addresses the decision-making problem since the limited buffer and energy resources constrain all nodes. Each IoT node must decide on whether to request a data transmission, to ask for a wireless energy transfer or to abstain and not take any action. When a UAV receives a request from an IoT device, either for data reception or wireless energy transmission, it has to accept or decline. In this paper, we aim to find a proper packet delivery and energy transfer policy according to the system state that maximizes the data transmission efficiency of the system. We first formulate the problem as a Markov Decision Process (MDP) to tackle the successive decision issues, to optimize a utility for each node upon a casual environment. As the MDP formalism achieves its limits when the interactions between different nodes are considered, we formulate the problem as a Graph-based MDP (GMDP). The transition functions and rewards are then decomposed into local functions, and a graph illustrates the dependency{\textquoteright} relations among the nodes. To obtain the optimal policy despite the system{\textquoteright}s variations, Mean-Field Approximation (MFA) and Approximate linear-programming (ALP) algorithms were proposed to solve the GMDP problem. {\textcopyright} 2020 Elsevier B.V.},
	keywords = {Antennas, Approximate linear programming, Approximation algorithms, Behavioral research, Data communication systems, Data transfer, Data transmission efficiency, Decision making, Decision making analysis, Decision-making problem, Energy harvesting, Energy resources, Energy transfer, Graph theory, Graphic methods, Inductive power transmission, Internet of things, Linear programming, Markov Decision Processes, Markov processes, Mean field approximation, Unmanned aerial vehicles (UAV), Wireless energy transfers, Wireless power transfer (WPT)},
	doi = {10.1016/j.simpat.2020.102102},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084066274\&doi=10.1016\%2fj.simpat.2020.102102\&partnerID=40\&md5=6a1c9e107244a170a782e61d0f9755cc},
	author = {Lhazmir, S. and Oualhaj, O.A. and Kobbane, A. and Mokdad, L.}
}
@article {11810056420151101,
	title = {Proposition of a new ex-ante evaluation method for adapting and selecting ERP solutions.},
	journal = {E-Ti: E-Review in Technologies Information},
	number = {8},
	year = {2015},
	pages = {34 - 47},
	abstract = {Acquiring an ERP system is one of the most risky, tedious and complex decision making activities for any organization. It has been widely reported that selecting an inappropriate ERP is one of the major reasons for its implementation failure. In this paper, we will develop a new ex-ante evaluation method for ERP system tailoring and selection. The proposed method, called SEVALERPS (Systematic Evaluation of ERP Systems), is basically elaborated to help organizations, especially large ones, to better customize and evaluate the potential ERP solutions in order to choose the ones that meet their best requirements{\textquoteright} tradeoff. SEVALERPS relies on many sound mathematical techniques to handle various evaluation aspects: 0-1 linear programming to choose the best ERP tailoring scenarios, MACBETH to express the preferences of the selection team in both a qualitative and quantitative way, and the discrete Choquet integral to address interdependencies that might exist among evaluation criteria. (En},
	keywords = {0-1 linear Programing, Adaptation ERP, Choquet Integral, Couverture fonctionnelle, Enterprise resource planning, ERP Evaluation, ERP Functional coverage, ERP Selection, ERP Tailoring, {\'E}valuation ERP, Int{\'e}grale de Choquet, Linear programming, MACBETH, Programmation lin{\'e}aire {\`a} variables binaires, S{\'e}lection ERP},
	issn = {11148802},
	url = {http://search.ebscohost.com/login.aspx?direct=true\&db=iih\&AN=118100564\&site=ehost-live},
	author = {Khaled, Abdelilah and Janati Idrissi, Mohammed Abdou}
}
@article {9954595520141215,
	title = {Solving a mixed integer linear program with times setup for the steel-continuous casting planning and scheduling problem.},
	journal = {International Journal of Production Research},
	volume = {52},
	number = {24},
	year = {2014},
	pages = {7276 - 7296},
	abstract = {In this paper, we present a novel model that generalise the steelmaking continuous casting planning and scheduling problem. The model includes three stages: converters namely CV, refining stands namely RS and continuous castings namely CC. The obtained problem can be formulated as a mathematical program with typical constraints, namely the times setup constraints. We develop a mixed integer linear program (MILP) to schedule several sequences of charges for more than two continuous castings devices. The aim is: (i) on one hand, to schedule a list of several sequences that are already ordered for each continuous casting with times setup between two successive sequences, (ii) on the other hand, to determine the optimal order of the successive sequences. We use a benchmark and randomly generated instances to test the model and solved by mean of the commercial software solverCplex v12.5. These problems span a variety of instances varying from small to large sized instances with different i},
	keywords = {Continuous casting, Linear programming, Mathematical models, Mathematical optimization, MILP, Mixed integer linear programming, optimisation, planning, Scheduling, setup, steel},
	issn = {00207543},
	url = {http://search.ebscohost.com/login.aspx?direct=true\&db=bth\&AN=99545955\&site=ehost-live},
	author = {Sbihi, Abdelkader and Bellabdaoui, Adil and Teghem, Jacques}
}
