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2019Ines Ben Jaafar
Modèles et Architectures d’agents pour les Problèmes d’Optimisation
Habilitation Universitaire, 2019
Abstract
Ce manuscrit présente une synthèse des travaux de recherche que j’ai effectués de 2007 à 2018 en tant que Maître Assistante, et chercheur depuis 1999 au sein de l’unité de recherche URIASIS qui était ensuite promue Laboratoire SOIE (et actuellement SMART) à l’ISG de Tunis.
Meriam Jemel, Nadia Ben Azzouna,RPMInter-work: a multi-agent approach for planning the task-role assignments in inter-organisational workflow
Enterprise Information Systems, 14(5), 611–640., 2019
Abstract
Workflow management is a core component of modern Enterprise Information Systems (EISs) infrastructure that automates the execution of critical business processes. One of the particular interests of the security community is how to ensure the completion of the workflow execution in the presence of authorisation constraints. These constraints present some restrictions on the users or the roles that are authorised to execute the workflow tasks. The goal is to enforce the legal assignments of access privileges to the executors of the workflow tasks. Despite the variety of approaches proposed in this context, an approach dedicated to the inter-organisational workflows is still missing. In this paper, we take a step towards this goal by proposing a multi-agent-based model, named RPMInter-Work (task-Role assignment Planning Model for Inter-organisational Workflow). Our approach aims to perform the planning of the task-role assignments in inter-organisational workflow in presence of authorisation constraints that are related to task-role assignments. In our research work, this planning problem is formulated as a DisCSP (Distributed Constraint Satisfaction Problem). Our proposed contribution is based on the requirements of inter-organisational workflows, in particular, the autonomy of the participating organisations and the respect of their privacy. A prototype of RPMInter-Work is implemented using JADE (Java Agent DEvelopment) platform and some evaluation results of this prototype are exposed in this paper.
, Moez Hammami,Hybrid Genetic Algorithm for CSOP to Find the Lowest Hamiltonian Circuit in a Superimposed Graph
Artificial Intelligence and Soft Computing, Springer International Publishing, 2019, pp 512--525, 2019
Abstract
Many fields use the graphs as a tool of representation such as multimodal networks, computer networks, wireless sensor networks, energy distribution. But, beyond the representation of data, the graphs also serve to propose solutions to certain problems mentioning the well-known problem finding the shortest Hamiltonian circuit in a graph. The aim of this paper is to elucidate a mechanism to obtain the most efficient Hamiltonian circuit among specified nodes in a given superimposed graphs (SGs). The Hamiltonian circuit is a circuit that visits each node on the graph exactly once. The SG represents a scheme of multimodal transportation systems and takes into account distance among other variables. The Hamiltonian path may be constructed and adjusted according to specific constraints such as time limits. This paper introduces new constraint satisfaction optimization problem formalism (CSOP) for the problem of finding the lowest Hamiltonian circuit in superimposed graphs, and as a resolution method, we use the genetic algorithm. As a case study, we adopt the transportation data of Guangzhou, in China.
, , Moez Hammami,A New Combination of Diversity Techniques in Ensemble Classifiers for Handling Complex Concept Drift
book-chapter in learning from data streams in evolving environments, pp 39-61. Springer International Publishing, January 2019., 2019
Abstract
Recent advances in Computational Intelligent Systems have focused on addressing complex problems related to the dynamicity of the environments. Generally in dynamic environments, data are presented as streams that may evolve over time and this is known by concept drift. Handling concept drift through ensemble classifiers has received a great interest in last decades. The success of these ensemble methods relies on their diversity. Accordingly, various diversity techniques can be used like block-based data, weighting-data or filtering-data. Each of these diversity techniques is efficient to handle certain characteristics of drift. However, when the drift is complex, they fail to efficiently handle it. Complex drifts may present a mixture of several characteristics (speed, severity, influence zones in the feature space, etc.) which may vary over time. In this case, drift handling is more complicated and requires new detection and updating tools. For this purpose, a new ensemble approach, namely EnsembleEDIST2, is presented. It combines the three diversity techniques in order to take benefit from their advantages and outperform their limits. Additionally, it makes use of EDIST2, as drift detection mechanism, in order to monitor the ensemble’s performance and detect changes. EnsembleEDIST2 was tested through different scenarios of complex drift generated from synthetic and real datasets. This diversity combination allows EnsembleEDIST2 to outperform similar ensemble approaches in terms of accuracy rate, and present stable behaviors in handling different scenarios of complex drift.
Abir Chaabani, Lamjed Ben SaidTransfer of learning with the coevolutionary decomposition-based algorithm-II: a realization on the bi-level production-distribution planning system.
Applied Intelligence, 49(3), 963- 982, 2019
Abstract
Bi-Level Optimization Problem (BLOP) is a class of challenging problems with two levels of optimization tasks. The main goal is to optimize the upper level problem, which has another optimization problem as a constraint. In this way, the evaluation of each upper level solution requires finding an optimal solution to the corresponding lower level problem, which is computationally so expensive. For this reason, most proposed bi-level resolution methods have been restricted to solve the simplest case (linear continuous BLOPs). This fact has attracted the evolutionary computation community to solve such complex problems. Besides, to enhance the search performance of Evolutionary Algorithms (EAs), reusing knowledge captured from past optimization experiences along the search process has been proposed in the literature, and was demonstrated much promise. Motivated by this observation, we propose in this paper, a memetic version of our proposed Co-evolutionary Decomposition-based Algorithm-II (CODBA-II), that we named M-CODBA-II, to solve combinatorial BLOPs. The main motivation of this paper is to incorporate transfer learning within our recently proposed CODBA-II scheme to make the search process more effective and more efficient. Our proposed hybrid algorithm is investigated on two bi-level production-distribution problems in supply chain management formulated to: (1) Bi-CVRP and (2) Bi-MDVRP. The experimental results reveal a potential advantage of memes incorporation in CODBA-II. Most notably, the results emphasize that transfer learning allows not only accelerating the convergence but also finding better solutions.
Malek Abbassi, Abir Chaabani, Lamjed Ben SaidAn investigation of a bi-level non-dominated sorting algorithm for production-distribution planning system
In International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems IEA AIE’19, china, 819- 826, 2019
Abstract
Bi-Level Optimization Problems (BLOPs) belong to a class of challenging problems where one optimization problem acts as a constraint to another optimization level. These problems commonly appear in many real-life applications including: transportation, game-playing, chemical engineering, etc. Indeed, multi-objective BLOP is a natural extension of the single objective BLOP that bring more computational challenges related to the multi-objective hierarchical decision making. In this context, a well-known algorithm called NSGA-II was presented in the literature among the most cited Multi-Objective Evolutionary Algorithm (MOEA) in this research area. The most prominent features of NSGA-II are its simplicity, elitist approach and a non-parametric method for diversity. For this reason, in this work, we propose a bi-level version of NSGA-II, called Bi-NSGA-II, in an attempt to exploit NSGA-II features in tackling problems involving bi-level multiple conflicting criteria. The main motivation of this paper is to investigate the performance of the proposed variant on a bi-level production distribution problem in supply chain management formulated as a Multi-objective Bi-level MDVRP (M-Bi-MDVRP). The paper reveals three Bi-NSGA-II variants for solving the M-Bi-MDVRP basing on different variation operators (M-VMX, VMX, SBX and RBX). The experimental results showed the remarkable ability of our adopted algorithm for solving such NP-hard problem.
, Ameni Azzouz, , , Lamjed Ben SaidA two-stage three-machine assembly scheduling problem with deterioration effect
International Journal of Production Research, 57(21), 6634-6647., 2019
Abstract
The two-stage assembly scheduling problem has received growing attention in the research community. Furthermore, in many two-stage assembly scheduling problems, the job processing times are commonly assumed as a constant over time. However, it is at odds with real production situations some times. In fact, the dynamic nature of processing time may occur when machines lose their performance during their execution times. In this case, the job that is processed later consumes more time than another one processed earlier. In view of these observations, we address the two-stage assembly linear deterioration scheduling problem in which there are two machines at the first stage and an assembly machine at the second stage. The objective is to complete all jobs as soon as possible (or to minimise the makespan, implies that the system can yield a better and efficient task planning to limited resources). Given the fact that this problem is NP-hard, we then derive some dominance relations and a lower bound used in the branch-and-bound method for finding the optimal solution. We also propose three metaheuristics, including dynamic differential evolution (DDE), simulated annealing (SA) algorithm, and cloud theory-based simulated annealing (CSA) algorithm for find near-optimal solutions. The performances of the proposed algorithms are reported as well.
Nadia Ben Azzouna,RPMInterwork: A multi-agent approach for planning task-role assignments in inter-organizational workflow
Enterprise Information Systems, 14(5), 611–640., 2019, 2019
Abstract
Workflow management is a core component of modern Enterprise Information Systems (EISs) infrastructure that automates the execution of critical business processes. One of the particular interests of the security community is how to ensure the completion of the workflow execution in the presence of authorisation constraints. These constraints present some restrictions on the users or the roles that are authorised to execute the workflow tasks. The goal is to enforce the legal assignments of access privileges to the executors of the workflow tasks. Despite the variety of approaches proposed in this context, an approach dedicated to the inter-organisational workflows is still missing. In this paper, we take a step towards this goal by proposing a multi-agent-based model, named RPMInter-Work (task-Role assignment Planning Model for Inter-organisational Workflow). Our approach aims to perform the planning of the task-role assignments in inter-organisational workflow in presence of authorisation constraints that are related to task-role assignments. In our research work, this planning problem is formulated as a DisCSP (Distributed Constraint Satisfaction Problem). Our proposed contribution is based on the requirements of inter-organisational workflows, in particular, the autonomy of the participating organisations and the respect of their privacy. A prototype of RPMInter-Work is implemented using JADE (Java Agent DEvelopment) platform and some evaluation results of this prototype are exposed in this paper.
Nadia Ben Azzouna,RPMInter-work: a multi-agent approach for planning the task-role assignments in inter-organisational workflow
Enterprise Information Systems, 14(5), 611–640., 2019, 2019
Abstract
Workflow management is a core component of modern Enterprise Information Systems (EISs) infrastructure that automates the execution of critical business processes. One of the particular interests of the security community is how to ensure the completion of the workflow execution in the presence of authorisation constraints. These constraints present some restrictions on the users or the roles that are authorised to execute the workflow tasks. The goal is to enforce the legal assignments of access privileges to the executors of the workflow tasks. Despite the variety of approaches proposed in this context, an approach dedicated to the inter-organisational workflows is still missing. In this paper, we take a step towards this goal by proposing a multi-agent-based model, named RPMInter-Work (task-Role assignment Planning Model for Inter-organisational Workflow). Our approach aims to perform the planning of the task-role assignments in inter-organisational workflow in presence of authorisation constraints that are related to task-role assignments. In our research work, this planning problem is formulated as a DisCSP (Distributed Constraint Satisfaction Problem). Our proposed contribution is based on the requirements of inter-organisational workflows, in particular, the autonomy of the participating organisations and the respect of their privacy. A prototype of RPMInter-Work is implemented using JADE (Java Agent DEvelopment) platform and some evaluation results of this prototype are exposed in this paper.
Meriam Jemel, Nadia Ben Azzouna,RPMInterwork: A multi-agent approach for planning task-role assignments in inter-organizational workflow
the Journal of Enterprise Information Systems, Taylor & Francis, 2019, 2019
Abstract
Workflow management is a core component of modern Enterprise Information Systems (EISs) infrastructure that automates the execution of critical business processes. One of the particular interests of the security community is how to ensure the completion of the workflow execution in the presence of authorisation constraints. These constraints present some restrictions on the users or the roles that are authorised to execute the workflow tasks. The goal is to enforce the legal assignments of access privileges to the executors of the workflow tasks. Despite the variety of approaches proposed in this context, an approach dedicated to the inter-organisational workflows is still missing. In this paper, we take a step towards this goal by proposing a multi-agent-based model, named RPMInter-Work (task-Role assignment Planning Model for Inter-organisational Workflow). Our approach aims to perform the planning of the task-role assignments in inter-organisational workflow in presence of authorisation constraints that are related to task-role assignments. In our research work, this planning problem is formulated as a DisCSP (Distributed Constraint Satisfaction Problem). Our proposed contribution is based on the requirements of inter-organisational workflows, in particular, the autonomy of the participating organisations and the respect of their privacy. A prototype of RPMInter-Work is implemented using JADE (Java Agent DEvelopment) platform and some evaluation results of this prototype are exposed in this paper.
