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2015Slim Bechikh, Abir Chaabani, Lamjed Ben Said
An efficient chemical reaction optimization algorithm for multi-objective optimization
IEEE transactions on cybernetics, 45(10), 2051-2064, 2015
Abstract
Recently, a new metaheuristic called chemical reaction optimization was proposed. This search algorithm, inspired by chemical reactions launched during collisions, inherits several features from other metaheuristics such as simulated annealing and particle swarm optimization. This fact has made it, nowadays, one of the most powerful search algorithms in solving mono-objective optimization problems. In this paper, we propose a multiobjective variant of chemical reaction optimization, called nondominated sorting chemical reaction optimization, in an attempt to exploit chemical reaction optimization features in tackling problems involving multiple conflicting criteria. Since our approach is based on nondominated sorting, one of the main contributions of this paper is the proposal of a new quasi-linear average time complexity quick nondominated sorting algorithm; thereby making our multiobjective algorithm efficient from a computational cost viewpoint. The experimental comparisons against several other multiobjective algorithms on a variety of benchmark problems involving various difficulties show the effectiveness and the efficiency of this multiobjective version in providing a well-converged and well-diversified approximation of the Pareto front.
Abir Chaabani, Slim Bechikh, Lamjed Ben SaidA Co-Evolutionary Decomposition-based Algorithm for Bi-Level combinatorial Optimization
IEEE Congress on Evolutionary Computation CEC’15, Japan, 1659-1666, 2015
Abstract
Several optimization problems encountered in practice have two levels of optimization instead of a single one. These BLOPs (Bi-Level Optimization Problems) are very computationally expensive to solve since the evaluation of each upper level solution requires finding an optimal solution for the lower level. Recently, a new research field, called EBO (Evolutionary Bi-Level Optimization) has appeared thanks to the promising results obtained by the use of EAs (Evolutionary Algorithms) to solve such kind of problems. Most of these promising results are restricted to the continuous case. Motivated by this observation, we propose a new bi-level algorithm, called CODBA (CO-Evolutionary Decomposition based Bi-level Algorithm), to tackle combinatorial BLOPs. The basic idea of our CODBA is to exploit decomposition, parallelism, and co-evolution within the lower level in order to cope with the high computational cost. CODBA is assessed on a set of instances of the bi-level MDVRP (MultiDepot Vehicle Routing Problem) and is confronted to two recently proposed bi-level algorithms. The statistical analysis of the obtained results shows the merits of CODBA from effectiveness and efficiency viewpoints.
Abir Chaabani, Slim Bechikh, Lamjed Ben Said,An improved co-evolutionary decomposition-based algorithm for bi-level combinatorial optimization
Conference on Genetic and Evolutionary Computation GECCO’15, Spain, 1363-1364, 2015
Abstract
Several real world problems have two levels of optimization instead of a single one. These problems are said to be bi-level and are so computationally expensive to solve since the evaluation of each upper level solution requires finding an optimal solution at the lower level. Most existing works in this direction have focused on continuous problems. Motivated by this observation, we propose in this paper an improved version of our recently proposed algorithm CODBA (CO-evolutionary Decomposition-Based Algorithm), called CODBA-II, to tackle bi-level combinatorial problems. Differently to CODBA, CODBA-II incorporates decomposition, parallelism, and co-evolution within both levels: (1) the upper level and (2) the lower one, with the aim to further cope with the high computational cost of the over-all bi-level search process. The performance of CODBA-II is assessed on a set of instances of the MDVRP (Multi-Depot Vehicle Routing Problem) and is compared against three recently proposed bi-level algorithms. The statistical analysis of the obtained results shows the merits of CODBA-II from effectiveness viewpoint.
Ameni Azzouz, Meriem Ennigrou, Boutheina JLIFIDiversifying TS using GA in multi-agent system for solving flexible job shop problem
12th International Conference on Informatics in Control, Automation and Robotics (ICINCO). Vol. 1. IEEE, 2015., 2015
Abstract
No doubt, the flexible job shop problem (FJSP) has an important significance in both fields of production management and combinatorial optimization. For this reason, FJSP continues to attract the interests of researchers both in academia and industry. In this paper, we propose a new multi-agent model for FJSP. Our model is based on cooperation between genetic algorithm (GA) and tabu search (TS). We used GA operators as a diversification technique in order to enhance the searching ability of TS. The computational results confirm that our model MAS-GATS provides better solutions than other models.
Meriam Jemel, Nadia Ben Azzouna,ECA rules for controlling authorisation plan to satisfy dynamic constraints.
. In Proceedings of the 13th Annual Conference on Privacy, Security and Trust (PST 2015), November 26-28 2015, Aksaray, Turkey, pages 133-138, IEEE Computer Society, 2015, 2015
Abstract
The workflow satisfiability problem has been studied by researchers in the security community using various approaches. The goal is to ensure that the user/role is authorised to execute the current task and that this permission doesn’t prevent the remaining tasks in the workflow instance to be achieved. A valid authorisation plan consists in affecting authorised roles and users to workflow tasks in such a way that all the authorisation constraints are satisfied. Previous works are interested in workflow satisfiability problem by considering intra-instance constraints, i.e. constraints which are applied to a single instance. However, inter-instance constraints which are specified over multiple workflow instances are also paramount to mitigate the security frauds. In this paper, we present how ECA (Event-Condition-Action) paradigm and agent technology can be exploited to control authorisation plan in order to meet dynamic constraints, namely intra-instance and inter-instance constraints. We present a specification of a set of ECA rules that aim to achieve this goal. A prototype implementation of our proposed approach is also provided in this paper.
Mouna Belhaj, , Lamjed Ben SaidModelling and simulation of human behavioural and emotional dynamics during emergencies: A review of the state-of-the-art
International Journal of Emergency Management, 11(2), 129-145., 2015
Abstract
Research works on human behaviour modelling and simulation
continue to increase in recent years. Indeed, emotion and personality are amongthe most important human characteristics that influence behaviour. Particularly, during emergencies, emotional dynamics have a major influence on individual
and collective behaviours. In this paper, we aim to provide an integrated review on this challenging and multidisciplinary field. We give first an overview of computational models of emotions and personalities. Then, we expose and discuss emotional and behavioural models. An emphasis is given to the role of
internal and external emotional dynamics in the production of realistic behaviours during emergencies. Internal emotional dynamics affect cognitive processes at an individual level. However, external emotional dynamics, studied through phenomena such as empathy or emotional contagion, are
essential to simulate collective emotional dynamics.Hanen Lejmi, Lamjed Ben Said,Agent-based modeling and simulation of the emotional experiences of employees within organizations
Agent-based modeling and simulation of the emotional experiences of employees within organizations, 2015
Abstract
Agent-Based Modeling and Simulation (ABMS) have been used to study a wide range of complex systems and several emergent behaviors across a variety of disciplines. However, very limited works have adopted these paradigms to provide insights to organizational psychology in general and to researches dealing with emotions at work in particular. The current research uses ABMS to study the emotions experienced in the organizational context; it focuses specifically on their impact on the quality of decisions made as a key factor of organizations success. In this paper, the emphasis is set on the emotion generation process. The proposed work introduces an agent-based model of the emotional experiences of employees within organizations. It adopts a cross-disciplinary approach and it brings another theoretical perspective to agent-based modeling of emotions at work. In fact, this model is based on the OCC appraisal theory to generate artificial emotions, but it also takes advantage of theoretical foundations from organization behavior and organization psychology. Simulation results can bring new insights to organizational researches. Moreover, the simulated system can serve as a human resources development tool used by employees at work to enhance their emotional awareness.
Hanen Lejmi, Lamjed Ben Said,Computational Models of Immediate and Expected Emotions for Emotional BDI Agents
Computational Models of Immediate and Expected Emotions for Emotional BDI Agents, 2015
Abstract
In line with the multi-disciplinary growing interest in emotions and the scientific proof of their usefulness for taking decisions, scholars, in agent-oriented systems, start to account for emotions when building upon intelligence and realism in rational agents. As a result, several computational models of emotions were developed and new architectures for emotional artificial agents were proposed, in particular the Emotional Belief Desire Intention (EBDI) agents. In this paper, we provide a comprehensive description of two computational models which are used to generate immediate and expected emotions. These models will be incorporated within an EBDI agent architecture that takes into consideration these two types of emotions.
Saoussen Bel Haj Kacem, ,Extended symbolic approximate reasoning based on linguistic modifiers
Knowledge and Information Systems, 42(3), 633-661, 2015., 2015
Abstract
Approximate reasoning allows inferring with imperfect knowledge. It is based on a generalization of modus ponens (MP) known as generalized modus ponens (GMP). We are interested in approximate reasoning within symbolic multi-valued logic framework. In a previous work, we have proposed a new GMP based on linguistic modifiers in the multi-valued logic framework. The use of linguistic modifiers allows having a gradual reasoning; moreover, it allows checking axiomatics of approximate reasoning. In this paper, we extend our approximate reasoning to hold with complex rules, i.e., rules whose premises are conjunction or disjunction of propositions. For this purpose, we introduce a new operator that aggregates linguistic modifiers and verifies the required properties of logical connectives within the multi-valued logic framework.
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2014, ,
Extending Policy Languages for Expressing the Self- Adaptation of Web Services
Journal of Universal Computer Science, 2014
Abstract
With the growing demand on Web Services, self-adaptation in the highly-dynamic
environment is becoming a key capability of service-based systems. As a solution for Web
services to provide added value and high QoS, combining self-* and policies allows reducing
management complexity and effectively drives adaptation. Also, providers must participate in
the self-adaptation process as they are aware of the capabilities of their offered services and
exceptions that may occur. Despite the important role of service providers, existing approaches
did not address this major issue. Thus, the description of self-adaptive Web services must not
be limited to functional and QoS data. To address these issues, we extend the WS-Policy
framework to represent capabilities and requirements of self-* Web services. We also extend
UDDI in order to store and manage service policies, as the current UDDI model does not offer
these capabilities. Finally, we propose an ECA-based planning mechanism to specify decision
making in the self-adaptation process.
