Personne :
Gaudreault, Jonathan

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Gaudreault
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Jonathan
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Université Laval. Département d'informatique et de génie logiciel
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ncf10571965
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  • Publication
    Restreint
    Agent-based supply-chain planning in the forest products industry
    (Springer, 2008-02-02) Frayret, Jean-Marc; Gaudreault, Jonathan; Rousseau, Alain N.; Harvey, Steve; D'Amours, Sophie
    The new economic challenges and recent trends in globalization have made it very difficult for Canadian forest product companies to improve their financial position without the coordinated involvement of the entire company, including their supply chains (distributed facilities, company offices, industrial customers, and distributors). Such a new level of efficiency involves their distributed facilities and offices spread around the world, and their customers. One consequence of this new reality is that forest products companies are now facing the need to re-engineer their organizational processes and business practices with their partners. To do this they must adopt new technologies to support the coordination of their planning and control efforts in a customer-centered environment. This paper first proposes a generic software architecture for development of an experimentation environment to design and test distributed advanced planning and scheduling systems. This architecture enables combination of agent-based technology and operations research-based tools in order to first take advantage of the ability of agent technology to integrate distributed decision problems, and, second, to take advantage of the ability of operations research to develop and exploit specific normative decision models. Next, this paper describes how this architecture has been configured into an advanced planning and scheduling tool for the lumber industry. Finally, we present how an application of this advanced planning tool is currently being validated and tested in a real manufacturing setting.
  • Publication
    Restreint
    Intégration d'outils APS dans une simulation multi-agent : une application à l'industrie du bois d'œuvre
    (Tec & Doc, 2008-01-01) Frayret, Jean-Marc; Gaudreault, Jonathan; Lemieux, Sébastien; D'Amours, Sophie
    Ces travaux proposent l’intégration d’un système avancé de planification pour l’industrie du sciage de bois résineux dans une simulation multi-agent. L’objectif visé est de permettre la simulation de différences conditions du marché afin de d’évaluer et de comparer l’impact économique de stratégies de pilotage ou de gestion de la demande dans un réseau de création de valeur. Dans cet article, un simulateur à base d’agents est présenté de même qu’un agent simulant le comportement des clients. Un cas d’étude (Virtual Lumber Case) est présenté afin d’illustrer le potentiel d’utilisation du simulateur. Ce cas représente une entreprise canadienne de production de bois d’œuvre, de taille moyenne. Le développement du cas VLC constitue un maillon clé dans le développement de cette recherche; il facilite la création de scénarios de simulation et l’étude de différentes stratégies propres à l’industrie des produits forestiers.
  • Publication
    Restreint
    Chaînes de création de valeur
    (Éditions MultiMondes, 2009-01-01) Martel, Alain; Frayret, Jean-Marc; Gaudreault, Jonathan; D'Amours, Sophie; LeBel, Luc
  • Publication
    Restreint
    Study of the performance of multi-behaviour agents for supply chain planning
    (Elsevier, 2009-06-30) Frayret, Jean-Marc; Gaudreault, Jonathan; Forget, Pascal; D'Amours, Sophie
    In today's industrial context, competitiveness is closely associated to supply chain performance. Coordination between business units is essential to increase this performance, in order to produce and deliver products on time to customers, at a competitive price. While planning systems usually follow a single straightforward production planning process, this paper proposes that partners adapt together their local planning process (i.e. planning behaviours) to the different situations met in the supply chain environment. Because each partner can choose different behaviour and all behaviours will have an impact on the overall performance, it is difficult to know which is preferable for each partner to increase their performance. Using agent-based technology, simulation experiments have been undertaken to verify if multi-behaviour planning agents who can change planning behaviours to adapt to their environment can increase supply chain performance. These agents have been implemented in an agent-based planning platform, using a case study illustrating a lumber supply chain. The performance analysis shows that advanced planning systems can take advantage of using multiple planning processes, because of the dynamic context of supply chains.
  • Publication
    Accès libre
    Machine learning-based models of sawmills for better wood allocation planning
    (Elsevier, 2020-03-11) Morin, Michael; Gaudreault, Jonathan; Brotherton, Edith; Paradis, Frédérik; Rolland, Amélie; Wéry, Jean; Laviolette, François
    The forest-products supply chain gives rise to a variety of interconnected problems. Addressing these problems is challenging, but could be simplified by rigorous data analysis through a machine learning approach. A large amount of data links these problems at various hierarchical levels (e.g., strategic, tactical, operational, online) which complicates the data computation phase required to model and solve industrial problem instances. In this study, we propose to use machine learning to generate models of the sawmills (converting logs into lumber) to simplify the data computation phase for solving optimization problems. Specifically, we show how to use these models to provide a recommendation for the allocation of cutblocks to sawmills for a wood allocation planning problem without needing extensive sawing simulations. Our experimental results on an industrial problem instance demonstrate that the generated models can be used to provide high-quality recommendations (sending the right wood to the right mill). Machine learning models of the sawmill transformation process from logs to lumber allows a better allocation exploiting the strengths of the mills to process the logs in our industrial case.
  • Publication
    Restreint
    Combined planning and scheduling in a divergent production system with co-production : a case study in the lumber industry
    (Elsevier, 2010-11-20) Frayret, Jean-Marc; Gaudreault, Jonathan; Rousseau, Alain N.; D'Amours, Sophie
    Many research initiatives carried out in production management consider process planning and operations scheduling as two separate and sequential functions. However, in certain contexts, the two functions must be better integrated. This is the case in divergent production systems with co-production (i.e. production of different products at the same time from a single product input) when alternative production processes are available. This paper studies such a context and focuses on the case of drying and finishing operations in a softwood lumber facility. The situation is addressed using a single model that simultaneously performs process planning and scheduling. We evaluate two alternative formulations. The first one is based on mixed integer programming (MIP) and the second on constraint programming (CP). We also propose a search procedure to improve the performance of the CP approach. Both approaches are compared with respect to their capacity to generate good solutions in short computation time.
  • Publication
    Accès libre
    Kriging analysis of an integrated demand management process in softwood industry
    (Elsevier, 2017-10-18) Gaudreault, Jonathan; Carle, Marc-André; Ben Ali, Maha; D'Amours, Sophie
    Objective: This paper aims to develop a basic understanding of a demand management process integrating sales and operations planning (S&OP) and order promising in a Make-To-Stock environment and to compare different demand management policies. Contribution: Typical researches about demand management processes analyze few system specifications or vary few potential factors one at time. Yet, we can get additional insights by employing design of experiments (DOE). Methodology: For making promises, we compare a First-Come First-Served approach to an approach using nested booking limits and giving advantage to profitable customers and attractive periods. Considering various sequences of order arrival, we generate Kriging metamodels that best describe the nonlinear relationships between the simulation responses and system factors for Canadian softwood lumber firms. We employ a Latin hypercube design to take into account different environmental scenarios. Results: Our analysis reveals the potential to improve the performance of the demand management process if we know high-priority customers needs before fulfilling less-priority orders and if we use nested booking limits concept.
  • Publication
    Restreint
    Optimization/simulation-based framework for the evaluation of supply chain management policies in the forest product industry
    (Institute of Electrical and Electronic[s] Engineers, 2012-12-13) Bouchard, Mathieu; Nour El Fath, Mustapha; Marier, Philippe; Gaudreault, Jonathan; Jerbi, Wassim; Lemieux, Sébastien; D'Amours, Sophie
    This work describes a framework for the elaboration and evaluation of management policies for production and transportation supply chains in the forest product industry. The approach deals with the issue of coordination between the tactical and operational decision levels. First, we introduce LogiLab, a software system allowing to model the network and to optimize product flows in the supply chain. We than show how one can use this tactical aggregated plan to identify management policies that will guide day to day operations at the operational level. Finally, a discrete event simulation model allows assessing with more details what would be the impact of implementing these policies at the operational/execution level.
  • Publication
    Restreint
    Motivations for multi behavior agents in supply chain planning
    (Édition Tec & doc-Lavoisier, 2008-01-01) Frayret, Jean-Marc; Gaudreault, Jonathan; Forget, Pascal; D'Amours, Sophie
    In today’ industrial context competitiveness is closely associated to supply chain performance. Coordiantion between production partners is essential in supply chains to deliver products on time to final clients. As perturbations occur all the time, production centers have to react quickly correct deviances and create new plans, while coordinating changes with partners. Agent-based technology provides a natural approach to model supply chain networks and describe specialized planning agents. To coordinate and optimize their production plan, agents ue specify the heuristic parameters a priori, at the time of their design and prior to their use. The solution proposed here is to give agents the opportunity to change these parameters, modifying their planning behaviors following the environmental conditions met. Using simulation, agents can identify optimal team behaviors for the supply chain in different situations. This paper explains the methodology followed to experiment multi-behavior agents and presents results from an application to the lumber supply chain.
  • Publication
    Accès libre
    Distributed operations planning in the softwood lumber supply chain : models and coordination
    (Centre interuniversitaire de recherche sur les réseaux d'entreprises, la logistique et le transport, 2009-02-01) Frayret, Jean-Marc; Gaudreault, Jonathan; Rousseau, Alain N.; Forget, Pascal; D'Amours, Sophie
    Agent-based technology provides a natural approach to model supply chain networks. Each production unit, represented by an agent, is responsible for planning its operations and uses communication to coordinate with the others. In this paper, we study a softwood lumber supply chain made of three planning units (sawing unit, drying unit and finishing unit). We define the problems and propose agent-specific mathematical models to plan and schedule operations. Then, in order to coordinate these plans between the three agents, we propose different coordination mechanisms. Using these developments, we show how an agent-based simulation tool can be used to integrate planning models and evaluate different coordination mechanisms.