Prof. Dr. Ahmed Frikha
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Academic Career Length
18Years (2009-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications30 November 2011 in International Journal of Approximate Reasoning
Journal Article
MBMohamed Ayman Boujelben
Mohamed Ayman Boujelben
YSYves De Smet
Yves De SmetAhmed FrikhaHCHabib Chabchoub
Habib Chabchoub30 September 2009 in International Journal of Approximate Reasoning
Journal Article
MBMohamed Ayman Boujelben
Mohamed Ayman Boujelben
YSYves De Smet
Yves De SmetAhmed FrikhaHCHabib Chabchoub
Habib ChabchoubJournal Article
CAChaima Ben Abdallah
Chaima Ben Abdallah
Adnen El-AmraouiFDFrancois Delmotte
Francois DelmotteAhmed FrikhaThis paper presents an innovative approach for supplier selection (SS) within the Tunisian dairy industry, with a specific focus on sustainability and resilience. The proposed method is a hybrid model that integrates multi-criteria decision-making (MCDM) with fuzzy logic. Initially, twelve distinct criteria are identified, categorized into social, environmental, economic, and resilience indexes through a combination of literature review and expert input. To establish the importance of these criteria, a fuzzy analytic hierarchy process (FAHP) is employed to calculate their weights. These weights are then integrated into a new method called fuzzy multi-attribute border approximation area comparison (FMABAC) to rank the suppliers. The methodology aims to provide decision-makers with a more intuitive means of expressing their preferences and evaluating supplier criteria, ultimately identifying the most effective dairy farmers. The research concludes by evaluating the results through two sensitivity analyses: one involving varying criteria weights and the other involving a comparative assessment with alternative fuzzy MCDM techniques.
Journal Article
MEMohamed Ali Elleuch
Mohamed Ali ElleuchMMMarwa Mallek
Marwa MallekAhmed Frikha
Wafik Hachicha
Awad AljuaidMAMURAD ANDEJANY
MURAD ANDEJANYIn recent years, the evaluation of several energy sources is an extremely significant issue that affects socio-environmental development and techno-economic growth in different sectors. To tackle this concern, many researchers have concentrated on preferring desirable energy sources and adopting multi-criteria group decision-making (MCGDM) approaches for only a single type of user (e.g., agricultural, industrial, tourism, or domestic users). However, every energy user plays an important role in shaping energy policy. In fact, for sustainable energy, it is important to include all main energy users at the same time in energy decision-making. The main objective of this work was to propose a fuzzy MCGDM approach to evaluate and prioritize energy sources in Tunisia from various sectors’ point of views. Many criteria are combined, including the following: technical, economic, social, political and environmental. After applying the fuzzy Delphi method, the proposed approach consists of applying a fuzzy TOPSIS method as a multi-criteria approach. Finally, a sensitivity analysis is performed to evaluate the results of the proposed approach and to study how the optimal solution is affected by the objective function coefficients.
Journal Article
ZKZainab KOUBAA
Zainab KOUBAAAdnen El-AmraouiAhmed FrikhaFDFrancois Delmotte
Francois DelmotteSustainable electricity consumption is considered a pivotal element in the effective governance and growth of any institution. Accurate electricity demand forecasting is essential for strategic planning and decision making. However, due to the numerous existing forecasting approaches, many forecasters find it challenging to select the best model. Currently, there is no robust approach for selecting the best forecasting model when considering conflicting error measures. This paper proposes a novel methodology using a multicriteria decision making (MCDM) approach to determine the most appropriate forecasting model for electricity demand, considering various interdependent error measures. The Analytical Network Process (ANP) was applied to determine the weights of evaluation criteria, while the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was employed to select the best forecasting model. The proposed methodology was tested and validated with a real case study in Tunisia using the opinions of experts and stakeholders. The results show that multiple regression and exponential smoothing are the best alternatives and outperformed the other models. Additionally, a sensitivity analysis is presented to test the robustness of the final ranking. This serves to assist decision makers to select the best forecasting model.
1 May 2011
Conference Paper
MSMezghani Salma
Mezghani Salma
Ahmed FrikhaWe treat a practical application of packing problem in supply chain management. This study was motivated by a real situation encountered in the storage problem of a foam industry in Tunisia. The storage problem consists in allocating, without overlapping, a given set of rectangular items (mattresses) to the minimum number of three dimensional bins with the different bins (rack) dimensions as input variables. Storage problem is a variable - sized bin packing problem that consists in finding an arrangement of set of items that cannot be rotated into the minimum number of variables bins. We develop a new heuristic method and we propose an integer programming model for the storage problem. The algorithm was applied in the case of unlimited number of bins. Numerical results on real-life test instances are reported.
About Me
Ahmed FRIKHA is a full professor in operational research at the Higher Institute of Industrial Management (ISGIS - University of Sfax) in which he occupied various administrative positions. He was elected as the director of the ISGIS since July 2014 until December 2020. He is a member of many research projects. Actually, He is the President of the Industrial Engineering Theses Committee. He is also member of organization and scientific committees of several conferences. In addition, he serves as a reviewer for several referred conferences and journals in his field. As a member of OLID research lab, his main research interests are focused on multi-criteria decision-making (MCDM), sustainable and resilient supply chains, and operations research. He explored the integration of artificial intelligence into lean and green management systems, particularly within Industry 4.0 and 5.0 frameworks. He also worked on circular economy models and the optimization of complex systems in logistics, healthcare, and agri-food sectors. He has published many papers in international journals and presented several communications. In addition, he is supervising multiple PhD theses. Over more than 23 years of teaching experience, he taught several courses. His teaching activities are focused on operational research, mathematical programming, decision theory, information theory, manufacturer systems, production management, project management and so on.