
Mahdi A. KhemakhemNational School of Electronics and Telecommunications - University of Sfax
Mahdi A. Khemakhem
Doctor of Engineering
About
58
Publications
14,635
Reads
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612
Citations
Introduction
My research activities are in the general area of artificial intelligence and combinatorial optimization. They are mainly focused on: (i) Designing efficient algorithms for solving combinatorial optimization problems, (ii) Developing mathematical models for complex systems, (iii) Developing solution procedures using Heuristics, Meta-Heuristics, Math-Heuristics, Hyper-Heuristics and Exact Algorithms, and (iv) Focusing on providing efficient and effective managerial decisions.
Additional affiliations
February 2017 - October 2020
University of Sfax - National School of Electronics and Telecommunications
Position
- Professor (Associate)
August 2015 - present
September 2011 - February 2017
University of Sfax - National School of Electronics and Telecommunications
Position
- Professor (Assistant)
Education
January 2004 - February 2008
January 2004 - February 2008
September 2002 - July 2003
Publications
Publications (58)
The COronaVIrus Disease 2019 (COVID-19) pandemic is unfortunately highly transmissible across the people. In order to detect and track the suspected COVID-19 infected people and consequently limit the pandemic spread, this paper entails a framework integrating the machine learning (ML), cloud, fog, and Internet of Things (IoT) technologies to propo...
In a cloud computing environment, virtual machine placement (VMP) represents an important challenge to select the most suitable set of physical machines (PMs) to host a set of virtual machines (VMs). The challenge is how to find optimal or near-optimal solution effectively and efficiently especially when VMP is considered as a NP-hard problem. Howe...
div>The COronaVIrus Disease 2019 (COVID-19) pandemic is unfortunately highly transmissible across the people. Therefore, a smart monitoring system that detects and tracks the suspected COVID-19 infected persons may improve the clinicians decision-making and consequently limit the pandemic spread. This paper entails a new framework integrating the M...
div>The COronaVIrus Disease 2019 (COVID-19) pandemic is unfortunately highly transmissible across the people. Therefore, a smart monitoring system that detects and tracks the suspected COVID-19 infected persons may improve the clinicians decision-making and consequently limit the pandemic spread. This paper entails a new framework integrating the M...
Making resources closer to the user might facilitate the integration of new technologies such as edge, fog, cloud computing, and big data. However, this brings many challenges shall be overridden when distributing a real-time stream processing, executing multiapplication in a safe multitenant environment, and orchestrating and managing the services...
Data center network virtualization is being considered as a promising technology to provide a performance guarantee for cloud computing applications. One important problem in data center network virtualization technology is virtual data center (VDC) embedding, which handles the physical resource allocation to virtual nodes (virtual switches and vir...
The knapsack problem is one of the most investigated and applicable combinatorial optimization problems. In this paper we consider a generalized problem called the Multiple Knapsack Problem with Setup (MKPS) in which a set of families of items and a set of knapsacks are available. Each item is characterized by a knapsack-dependent profit and each f...
Improper waste management can cause environmental pollution, unpleasant odours, and growth of insects, rodents and worms; it may lead to transmission of diseases like typhoid, cholera, and hepatitis through injuries from sharps contaminated with human blood (Abdulla et al., 2008). This study discusses the off-site transport problem of infectious he...
In this paper we propose a new hybrid heuristic approach that combines the Quantum Particle Swarm Optimization technique with a local search method to solve the Multidimensional Knapsack Problem. The approach also incorporates a heuristic repair operator that uses problem-specific knowledge instead of the penalty function technique commonly used fo...
http://rdcu.be/nh17
In this paper, we address a rich Traveling Salesman Problem with Profits encountered in several real-life cases. We propose a unified solution approach based on variable neighborhood search. Our approach combines several removal and insertion routing neighborhoods and efficient constraint checking procedures. The loading proble...
Knapsack problems with Setups (KPS) have received increasing attention in recent research for their potential use in the modeling of various concrete industrial and financial problems, such as order acceptance and production scheduling. The KPS problem consists in selecting appropriate items, from a set of disjoint families of items, to enter a kna...
The Knapsack Problem with Setup (KPS) is a generalization of the classical Knapsack problem (KP), where items are divided into families. An individual item can be selected only if a setup is incurred for the family to which it belongs. This paper provides a dynamic programming (DP) algorithm for the KPS that produces optimal solutions in pseudo-pol...
Solving constrained optimization problems (COPs) is a challenging task. In this paper we present a new strategy for solving COPs called solve and decompose (or \( S \& D\) for short). The proposed strategy is a systematic iterative depth-first strategy that is based on problem decomposition. \( S \& D\) uses a feasible solution of the COP, found by...
We introduce, model and solve to optimality a rich multi-product, multi-period and multi-compartment vehicle routing problem with a required compartment cleaning activity. This real-life application arises in the olive oil collection process in Tunisia, where regional collection offices dispose of a fleet of vehicles to collect one or several grade...
Over the last years, several variants of multi-constrained Vehicle Routing Problems (VRPs) have been studied, forming a class of problems known as Rich Vehicle Routing Problems (RVRPs). The purpose of the paper is twofold: (i) to provide a comprehensive and relevant taxonomy for the RVRP literature and (ii) to propose an elaborate definition of RVR...
This study proposes a new hybrid heuristic approach that combines the quantum particle swarm optimization (QPSO) technique with a local search phase to solve the binary generalized knapsack sharing problem (GKSP). The approach also incorporates a heuristic repair operator that uses problem-specific knowledge instead of the penalty function techniqu...
We introduce, model and solve to optimality a rich multi-product, multi-period and multi-compartment vehicle routing problem with a required compartment cleaning activity. This real-life application arises in the olive oil collection process in Tunisia, where regional collection offices dispose of a fleet of vehicles to collect one or several grade...
Healthcare waste management is one of the most important environmental problems in the world and particularly in Tunisia, because of the potential environmental hazards and public health risks. The collection of infectious healthcare waste is a highly visible and important service that involves large expenditures. This study discusses the off-site...
The Knapsack Sharing Problem (KSP) is a variant of the well-known NP-Hard knapsack problem that has received a lot of attention from the researches as it appears into several real-world problems such as allocating resources, reliability engineering, cloud computing, etc. In this paper, we propose a hybrid approach that combines an Iterative Linear...
We present a Rich variant of the Profitable Tour Problem (RPTP) arising when customer requests involve several products and multi-compartment vehicles are used. The RPTP addressed may be considered as a variant of the capacitated profitable tour problem with time windows and incompatibility constraints. We propose a Variable Neighborhood Search Alg...
This paper proposes a new hybrid tree search algorithm to the Multidimensional Knapsack Problem MKP that effectively combines tabu search with a dynamic and adaptive neighborhood search procedure. The authors' heuristic, based on a filter-and-fan F&F procedure, uses a Linear Programming-based Heuristic to generate a starting solution to the F&F pro...
Over the last years various extensions of the Vehicle Routing Problem (VRP), considering complicated constraints encountered in the real-life, has been studied. These extensions are often coined as rich VRP. In this work, we tackle a rich VRP namely the Multi Compartment Multi Commodity Heterogeneous Fixed Fleet Vehicle Routing Problem with hard Ti...
Cette thèse aborde un problème de transport appelé le Problème de m-Tournées Sélectives (PmTS) ou ”Team Orienteering Problem” en anglais. Le PmTS consiste à construire m tournées pour une flotte de véhicules afin de desservir un sous-ensemble sélectionné de clients. Dans le PmTS un service est fourni à chaque client visité en contrepartie de quoi,...