Abstract

k-unob

Abstract

Suitable suppliers’ recommendation forms the basis for a successful procurement process. An automated personalization of procurement opportunities relies on the buyer and the seller profiles consistency. However, dealing with their profiles matching is not a trivial task. In fact, each contextual detail may play a crucial role in the decision making procedure especially when final users express very specific and variable needs in a heterogeneous and inconstant environment. In this paper, we designed and developed a multi agent system (MAS) for the supply chain automatization. It includes two supplier selection levels followed by a negotiation module relying on the handicraft woman online situation. Several handicraft business ontologies in addition to multi-side profile ontology are developed in order to drive the agent communication with the internal and external environment.

Abstract

En vue de s’approvisionner, les femmes artisanes brodeuses font face à divers problèmes. Disposer d’une vue globale portant sur les fournisseurs adaptés, les meilleures opportunités d’approvisionnement, ainsi que la gestion de rupture des stocks représentent un réel défit pour elles. Face à ces problèmes, les systèmes de recommandation ont montré leur performance en matière de personnalisation des connaissances accordées aux professionnels. Dans ce sens, nous proposons un prototype d’un système suggérant les fournisseurs de confiance les mieux adaptés par rapport au profil de la femme artisane en s’appuyant sur trois niveaux de sélection, suivis d’une phase de négociation. Le prototype proposé se base sur une architecture multi-agents et se sert d’une ontologie métier modélisant le métier de la broderie ainsi qu’une ontologie de profil permettant de définir les profils des acteurs métier.

In order to procure, the handicraft women (embroideresses), face various issues. Having a global overview on the suitable suppliers, the best procurement opportunities and the inventory shortage management represent a real challenge for them. To deal with these issues, the recommender systems have shown their performance in terms of the personalization of the knowledge provided to the professionals. In this respect, we propose a prototype for a system suggesting the trustworthy and suitable suppliers according to the handicraft woman profile and relying on three selection levels, followed by a negotiation phase. The proposed prototype is based on a multi-agents architecture and uses a business ontology modeling the embroidery business as well as profile ontology for setting the business actors’ profiles.

Abstract

Most biclustering algorithms for microarrays data analysis focus on positive correlations of genes. However, recent studies demonstrate that groups of biologically significant genes can show negative correlations as well. So, discovering negatively correlated patterns from microarrays data represents a real need. In this paper, we propose a Memetic Biclustering Algorithm (MBA) which is able to detect negatively correlated biclusters. The performance of the method is evaluated based on two well-known microarray datasets (Yeast cell cycle and Saccharomyces cerevisiae), showing that MBA is able to obtain statistically and biologically significant biclusters

Abstract

Abstract

We consider a supply chain consisting of a supplier and locations selling an innovative product. These locations could collaborate together by transshipment which is known as product transferring adopted mainly to reduce inventory costs and to improve customer service level. In this research, we are interested in the transshipment problem where the customer demands, the holding and the shortage costs are uncertain and represented by fuzzy sets. Our objectives are to propose a transshipment policy that takes into account the fuzziness of the mentioned parameters and to derive the approximate replenishment quantities. In order to achieve these objectives, we propose a transshipment decision process considering decision makers attitudes towards risks and a hybrid algorithm based on fuzzy simulation and genetic algorithm designed to determine the approximate replenishment quantities.

Abstract

Over the last decade, emotions have received considerable attention among scholars in agent oriented systems. In fact a large amount of computational models of emotions has been developed and a new generation of artificial agents has emerged to give rise to emotional agents, in particular the Emotional BDI (EBDI) agents. However, in spite of the several interesting studies that have been conducted to underline the role of emotions in decision-making, few works in the agent community have shed the light on the influences of both immediate and expected emotions to drive decision-making. In this context, we intend to propose a new conceptual model of EBDI agency that involves the interplay among immediate emotions, expected emotions and rational decisions of artificial agents.

Abstract

In online services, making anonymous transactions is a crucial need in order to ensure the user’s trust towards a particular service. In this context, anonymity quantification is required to provide at which level the e-service respects the user privacy regarding the link between his/her identity and actions. Most of the existing researches are limited to the anonymity quantification in a static way and based, mainly, on the user’s set size. In this paper, the authors propose a new multi-agent based approach for anonymity quantification in e-services considering dynamic and mobile environment’s characteristics. The authors’ quantification is based on the fuzzy logic. It is based not only on the anonymity set size, which is always known in advance, but also on a set of other criteria such as the number of users and the priori and posteriori knowledge about internal and external attackers of an e-service. The carried out experimentations show competitive and better results when compared to other recently proposed anonymity quantification.

Abstract

This paper introduces an organizational multi-agent model for crisis management. The considered crisis is a heavy snow storm, occurred at a north Tunisian delegation. The studied crisis caused severe infrastructure damages and endangered people’s lives. Crisis systems are generally made of several heterogeneous and autonomousorganizations. Each organization is given tasks and their tasks are strongly correlated. Organizations have to interact frequently and cooperate at a high level to deal with the crisis. In this context, thinking the crisis management at a macro level with an organizational view as well as structuring organizations’ communications and their functioning is a crucial requirement. Following this view, the main purpose of our work is to propose a multi-agent system organization that manages resources efficiently, structure the communication among all the actors involved in the crisis management and orchestrate their work. More precisely, we provide an environment model that identifies all concepts and entities involved in the snow storm crisis. We specify, using GAIA methodology, a multi-agent organizational model that defines the roles involved in the system and the interaction protocols to realize organizational objectives. Finally, a simulator has been implemented to demonstrate the feasibility of our approach.

Abstract

In this paper, we propose an Indicator-based Chemical Reaction Optimization (ICRO) algorithm for multiobjective optimization. There are two main motivations behind this work. On the one hand, CRO is a new recently proposed metaheuristic which demonstrated very good performance in solving several mono-objective problems. On the other hand, the idea of performing selection in Multi-Objective Evolutionary Algorithms (MOEAs) based on the optimization of a quality metric has shown a big promise in tackling Multi-Objective Problems (MOPs). The statistical analysis of the obtained results shows that ICRO provides competitive and better results than several other MOEAs.