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Bruno Agard

Affiliations: 
Mathematics and Industrial Engineering Ecole Polytechnique, Montreal (Canada) 
Area:
Industrial Engineering
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"Bruno Agard"
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Parents

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Michel Tollenaere grad student 2002 Institut National Polytechnique de Grenoble (INPG) (E-Tree)
 (Contribution à une méthodologie de conception de produits à forte diversité)

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Publications

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Dadouchi C, Agard B. (2020) Recommender systems as an agility enabler in supply chain management Journal of Intelligent Manufacturing. 1-20
Murray PW, Agard B, Barajas MA. (2018) ASACT - Data preparation for forecasting: A method to substitute transaction data for unavailable product consumption data International Journal of Production Economics. 203: 264-275
Daras G, Agard B, Penz B. (2018) A spatial data pre-processing tool to improve the quality of the analysis and to reduce preparation duration Computers & Industrial Engineering. 119: 219-232
Murray PW, Agard B, Barajas MA. (2018) Forecast of individual customer’s demand from a large and noisy dataset Computers & Industrial Engineering. 118: 33-43
Ghaemi MS, Agard B, Trépanier M, et al. (2017) A visual segmentation method for temporal smart card data Transportmetrica. 13: 381-404
Murray PW, Agard B, Barajas MA. (2017) Market segmentation through data mining: A method to extract behaviors from a noisy data set Computers & Industrial Engineering. 109: 233-252
Baud-Lavigne B, Agard B, Penz B. (2016) Simultaneous product family and supply chain design: An optimization approach International Journal of Production Economics. 174: 111-118
Homaie-Shandizi AH, Nia VP, Gamache M, et al. (2016) Flight deck crew reserve: From data to forecasting Engineering Applications of Artificial Intelligence. 50: 106-114
Baud-Lavigne B, Bassetto S, Agard B. (2016) A method for a robust optimization of joint product and supply chain design Journal of Intelligent Manufacturing. 27: 741-749
Moatari-Kazerouni A, Chinniah Y, Agard B. (2015) Integrating occupational health and safety in facility layout planning, part I: Methodology International Journal of Production Research. 53: 3243-3259
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