Mokhtar LAABIDI

Informations générales

Mokhtar LAABIDI
Grade

Doctorant

Biographie courte

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.

Publications

  • 2025
    Said 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 Said

    Ecological 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.

Projets