Informations générales
Doctorant
Mokhtar LAABIDI is a PhD researcher in multimodal transport optimization. His research focuses on developing mathematical models and multi-objective algorithms to enhance efficiency, sustainability, and resilience in supply chain management. His main interests include minimizing costs, transportation time, and CO₂ emissions.
Équipes
Publications
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2025Said Gattoufi, Nabil Ktifi, Mokhtar LAABIDI
Data Envelopment Analysis for Mergers and Acquisitions Transactions: Avenues of Research Toward Efficiency Gains
Data-envelopment-analysis-mergers-acquisitions, 2025
Résumé
The aim of this chapter is to explain in a simple way, without complications of mathematical modeling, a set of concepts and emphasize their interconnections and combinations in a large body of knowledge they created and emphasize the theoretical and applied benefits. In today's business world marked by profound changes and technological challenges, global companies are in fact developing strategies to improve their profitability and efficiency while adapting to geopolitical changes. To strengthen their resilience, they are increasingly turning to restructuring, partnership re-engineering, and mergers and acquisitions (M&A) to consolidate their market position and increase their chances of survival. This book chapter analyses in its first part a large set of research papers related to this topic. Among the approaches and methodologies adopted for analyzing this dynamic, we explain the Data Envelopment Analysis (DEA) methodology and its variants and emphasized on the assessment of the efficiency gains realized through mergers, acquisitions, takeovers, splits, consolidations and restructuring. The related literature, referenced in SCOPUS, is analyzed and the features of this literature are identified and analyzed, emphasizing the most influencing authors and the topics of their research. Finally, the concluding section synthetizes the interconnections between DEA and its variants as a tool from one side and the restructuring and consolidation dynamics of businesses, mainly M&A, from the other side. Several topics are suggested to widen this body of knowledge and boost its impact on goods and services industries and improve understanding production processes in a variety of sectors.Mokhtar LAABIDI, Lilia Rejeb, Lamjed Ben SaidEcological Multimodal Freight Transport Optimization
Selecting the most reliable stochastic routes requires the development of flexible, real-time, single-objective and multi-objective approaches based on technology and data analysis. In the, 2025
Résumé
Abstract—The increasing complexity of global supply chains,
combined with the need for fast, cost-effective, and environmentally
friendly deliveries, has reinforced the importance of
multimodal freight transportation(MFT) as a key solution to
meet modern demands. One of the main challenges in MFT
is to develop an innovative optimization model to plan and
manage the supply chain. In this work, we consider four
modes of transportation (air, road, rail, and sea) and propose
an innovative multi-objective optimization model, designed to
simultaneously minimize transportation costs, transit times,
and CO2 emissions, while integrating the complex operational
constraints inherent in current logistic systems. To address
this problem, we adopt two well-known algorithms : Non-
Dominated Sorting Genetic Algorithm III (NSGA-III) and
Teaching-Learning Optimization (TLBO), through an experimental
study demonstrating the effectiveness of these evolutionary
solution methods in solving these complex optimization
problem.
The results show that TLBO optimization effectively reduces
costs and environmental impact, while the NSGAIII algorithm
improves delivery times.
BibTeX
Gattoufi, S., Ktifi, N., & Laabidi, M. Data Envelopment Analysis for Mergers and Acquisitions Transactions: Avenues of Research Toward Efficiency Gains. In Decision Making Optimization Models for Business Partnerships (pp. 287-327). Chapman and Hall/CRC.
BibTeX
Mokhtar.L, Lilia.R and Lamhed.s, (2025). Ecological Multimodal Freight Transport Optimization (IEE conference CoDit 2025).
Projets
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2024Ameni Azzouz Abir Chaabani, Ameni Azzouz, Mokhtar LAABIDI, Chaouki Bayoudhi
Solving combinatorial optimization problems using advanced hybrid methods.
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