Bernard Espinasse

Toward a methodological framework for agent-based modelling and simulation of supply chains in a mass customization context

Abstract In a dynamic customer-centric supply chain context, classic forecasting models turn out to have a limited applicability. In order to estimate the key performance indices of these Supply Chains and to facilitate their management, it is necessary to use more elaborate tools such as a simulation. However building simulation of customer-centric supply chains is no trivial matter. It requires the elaboration of a representative model and the execution of this model according to a set of hypotheses associated to scenarios. Due to their properties, Multi-Agent Systems seem particularly well suited for the modelling and the simulation of Supply Chains and more especially in a mass customization context. In this paper we propose an agent modelling framework for the modelling and simulation of such Supply Chains to facilitate their management. We show how this framework can be applied to a case of customer-centric Supply Chain from the golf club industry and we present an experiment plan associated.

Multiagent Modeling and Simulation of Hydraulic Management of the Camargue

Modeling and simulation of human-influenced ecosystems require the integration of natural and decision-making processes. In such ecosystems, natural resource management aims at protecting natural areas while enabling human activities that contribute to these area characteristics. The object of this research is the modeling and simulation of the hydraulic management of the Camargue ecosystem with a multiagent system. The authors first present the problematics of this hydraulic management, its objectives, and a formalization of the different decision processes centered on a social contract and associated with two main phases: the contract elaboration phase and the contract realization phase. They present conceptual modeling and multiagent modeling of these two phases with details on agent models, agent behaviors, and negotiation models.

Environmental Decision Support System for Hydraulic Management of the Camargue: Functionalities and Software Architecture

The complexity of environmental dynamics makes more and more difficult the decision-making process. Therefore, the environmental managers, in particular in water management, rely on Environmental Decision Support Systems (EDSS) to help them. This paper defines the major generic functionalities of EDSS and the specific functionalities for an EDSS dedicated to the hydraulic management of the Camargue ecosystem. For this specific EDSS, a software architecture performing these functionalities is also proposed. Composed of functional modules and of an integration infrastructure inspired by HLA (High Level Architecture), this architecture would be reusable for development of other specific EDSS.

Cooperative disruption management in industrial systems: A multiagent approach

Abstract This paper presents a cooperative repair method for disruption management in industrial systems. Our method aims to enable industrial systems, and in particular workshops, to minimize the consequences of disruptions in their forecasted schedule. In order to define rescheduling measures proportional to a disruption importance, a set of distributed repair strategies, ranging from isolated to cooperative solving process, are defined. Agent based modelling is used to specify and operate these cooperative processes. Agent-based simulation illustrates the application of this method on a workshop where autonomous machines cooperate to manage disruptions.

A Methodological Approach for Agent Based Simulation of Mass Customizing Supply Chains

Mass customization has a significant impact on supply chains. The management of these highly dynamic organizations requires the development of adapted decision support systems. The agent approach appears fit for modelling and simulating mass customization supply chains. This paper presents a methodological approach for agent oriented modelling and simulation that is based on specific modelling levels and formalisms. The approach is illustrated through a case from the Golf industry.

Combining agents and Wrapper Induction for information gathering on restricted web domains

Web is growing constantly and exponentially every day. Thus, gathering relevant information becomes unfeasible. Existent indexing-based search engines ignore information context, which is essential to deciding on its relevance. Restraining to a single web domain, domain ontology can be used to take into consideration the related context, the fact that might enable treating web pages that belong to the considered domain more intelligently. Nevertheless, symbolic rules that exploit domains ontology to realize this treatment are delicate and fastidious to develop, especially for information extraction task. This paper presents Boosted Wrapper Induction (BWI), a machine learning method for adaptive information extraction, and its exploitation as a replacement of the symbolic approach for information extraction task in AGATHE, a generic multi-agent architecture for information gathering on restrained web domains.

AGATHE: An Agent- and Ontology-Based System for Gathering Information about Restricted Web Domains

Due to Web size and diversity of information, relevant information gathering on the Web turns out to be a highly complex task. The main problem with most information retrieval approaches is neglecting pages’ context, given their inner deficiency: search engines are based on keyword indexing which cannot capture context. Considering restricted domains, taking into account contexts may lead to more relevant and accurate information gathering. In the last years, we have conducted research with this hypothesis, and proposed an agent- and ontology-based restricted-domain cooperative information gathering approach accordingly, that permit the development of specific information gathering systems. In this article, we present this novel approach based on these guiding ideas, and a generic software architecture, named AGATHE, which is a full-fledged scalable multi-agent system.

Pyroxene: A Territorial Decision Support System Based on Spatial Simulators Integration for Forest Fire Risk Management

Medium term management of territorial risk increase requires decision support tools able to represent and simulate spatial dynamics. For forest fire risk, simulators of spatial dynamics of both fuel zones and vulnerable zones are produced by specialised disciplines, like ecology and geography. In order to integrate simulators of spatial dynamics of different themes at different scale levels, this paper proposes a spatial agent and GIS based software infrastructure called Pyroxene. This infrastructure is designed to implement “models for models integration†, specified by domain expert users. To do so, end users have to use a specification framework, specifically designed for spatio-dynamic models integration. The purpose of the implemented platform is to execute and synchronise integrated simulations. To operate the semantic and syntax requirements of such integration, the platform is structured in an HLA-like architecture, and implemented as a multi-agents system for models integration, compliant with the FIPA specification. It is also organised around a GIS. First steps of validation confirm the validity of the system at the functional level and precise the limits of using the approach on the operational level.

An agent-based and organisation oriented software architecture for supply chains simulation

The Supply Chain (SC) organizational structure and related management policies are crucial factors that can be adjusted to improve the SC performance, and tested through simulations. To facilitate the design of these simulations, we have proposed an agent-based methodological framework for SC modelling, taking into account observables of different levels of details and related to these SC organizational aspects. This paper describes an Agent-based software architecture, based on a mediator, enacting this methodological framework at a software level, to allow SC organisational-oriented simulation. This architecture can be seen as the interaction between different simulation platforms.

Decision Support for Forest Fire Risk Evaluation: Dynamic Modelling and Spatio-Temporal Integration

Land cover quickly changes in the Mediterranean area: forest progress on agricultural abandoned lands when scattered urban zone progress into forest areas. As forest fire risk in linked to spatial arrangements, land cover change implies quick changes in forest fire risk level. Cartographic fire risk models elaborated by research for engineering are usually static, and do not take into account this temporal dimension. However, decision-makers need risk change previews for judicious land management planning. A framework to integrate time in spatial risk models is proposed. It is funded on integration of land cover change (vegetation and urbanisation) dynamic models, and forest fire risk models in order to design an environmental decision support system (EDSS). Such a system has to integrate geographical information systems (GIS) with modelling and simulation softwares of land cover changes (vegetation, urbanisation). This spatio-temporal integration can take different forms, from weak coupling up to intelligent integration. Two integration strategies are studied.