Sébastien THOMASSEY

Associate Professor

Research

Human Centered Design Group

  • Research skill : Machine learning, Decision support system, Human Machine Interaction
  • Section CNU 61 – Génie informatique, automatique et traitement du signal

Research interests

  • Supply chain
  • Production management
  • Sales forecasting

PROJECTS

Below are the list of selected ongoing projects that Sébastien THOMASSEY is a Principal Investigator (PI) or co-PI

Camille 3D sensorielle (2011-2014)- Projet collaboratif FUI
Achille (2011-2013)- Projet collaboratif FP7 – ERA NET – CrossTexNet (7ème PCRD)
Maya (2012-2015)- Projet collaboratif FP7 – ERA NET – CrossTexNet (7ème PCRD)
INTELDALLE – (2013-2015)Projet collaboratif CrossTexNet (ERA-NET). 
SMDTex – (2012-2021)Projet Européen Eramus Mundus program, action 1, doctorat international (Sustainable Management and Design for Textiles)
DigTex (2016-2019)- Projet collaboratif FUI.
ECLin (2016-2019)– Projet région HDF financement 50 % Région, 50 % EcoTLC
FBD-BModels (2017-2020)- Projet Collaboratif Européen H2020. 
MDUQ (2018-2021)- Projet région HDF financement 50 % Région, 50 % ADEME.
Fashion Trends 4.0 (2019-2022)- Projet région HDF financement Région Hauts de France, I-SITE ULNE, Camaieu.
Cleantex (2020-2023)Projet ERASMUS+ 
Digital Fashion (2022-2025)- Projet ERASMUS+ 

BOOKS

2018

Thomassey S., Zeng X., 2018. Artificial Intelligence for Fashion Industry in the Big Data Era, Springer Singapore, ISBN : 978-981-13-0079-0, 

 

BOOK chapters

Harale N., Thomassey S., Zeng X., Small Series Fashion Supplier Selection using MCDM Methods. Chapter of: Multiple Criteria Decision Making Beyond the Information Age, Topcu Y.I., ÖzaydınO., KabakO., Ekici S.O. (Eds). Springer International Publishing, 2020. https://doi.org/10.1007/978-3-030-52406-7_8

He Z., Tran K.P., Thomassey S., Zeng X., Yi C., Application of Artificial Intelligence in Modeling a Textile Finishing Process. Chapter of: Reliability and Statistical Computing, Pham H. (eds). Springer Series in Reliability Engineering. Springer, 2020. https://doi.org/10.1007/978-3-030-43412-0_5

Ma K., Thomassey S., Zeng X., A New Collaborative Model for Demand-Driven Supply Chains: A Case Study on Textile Industry. Chapter of : Majumdar A., Gupta D., Gupta S. (eds) Functional Textiles and Clothing. Springer, Singapore, pp 339-347, 2019. https://doi.org/10.1007/978-981-13-7721-1_26

Giri C., Thomassey S., Zeng X., Customer Analytics in Fashion Retail Industry. Chapter of: Majumdar A., Gupta D., Gupta S. (eds) Functional Textiles and Clothing. Springer, Singapore, pp 349-361, 2019. https://doi.org/10.1007/978-981-13-7721-1_27

Thomassey S., Zeng X., Introduction: Artificial Intelligence for Fashion Industry in the Big Data Era. In : Thomassey S., Zeng X. (eds), Artificial Intelligence for Fashion Industry in the Big Data Era. Springer Series in Fashion Business. Springer, Singapore, pp 1-6, 2018. https://doi.org/10.1007/978-981-13-0080-6_1

Brahmadeep, Thomassey S., A Discrete Event Simulation Model with Genetic Algorithm Optimisation for Customised Textile Production Scheduling. In : Thomassey S., Zeng X. (eds), Artificial Intelligence for Fashion Industry in the Big Data Era. Springer Series in Fashion Business. Springer, Singapore, pp 153-171, 2018. https://doi.org/10.1007/978-981-13-0080-6_8

Xu Y., Thomassey S., Zeng X., AI for Apparel Manufacturing in Big Data Era : A Focus on Cutting and Sewing. In : Thomassey S., Zeng X. (eds), Artificial Intelligence for Fashion Industry in the Big Data Era, Springer Series in Fashion Business. Springer, Singapore, pp 125-151, 2018. https://doi.org/10.1007/978-981-13-0080-6_7

Brahmadeep, Thomassey, S., Intelligent demand forecasting systems for fast fashion, In: Choi T.M. (eds), Information Systems for the Fashion and Apparel Industry, Woodhead Publishing, pp. 145-161, 2016. https://doi.org/10.1016/B978-0-08-100571-2.00008-7

Brahmadeep, Thomassey S., Enterprise resource planning (ERP) systems for use in apparel supply chains, In: Choi T.M. (eds), Information Systems for the Fashion and Apparel Industry, Woodhead Publishing, pp. 235-261, 2016. https://doi.org/10.1016/B978-0-08-100571-2.00012-9

Thomassey S., Sales Forecasting in Apparel and Fashion Industry: A Review. In: Choi T.M., Hui CL., Yu Y. (eds), Intelligent Fashion Forecasting Systems: Models and Applications, Springer Berlin Heidelberg, pp. 9-27, 2014. https://doi.org/10.1007/978-3-642-39869-8_2

Ansel N, Thomassey S., Bruniaux P., Zeng, Z., Integration of an adaptive CAD system for flexible furniture industry, In: Zeng X., Li Y., Ruan D., Koehl L. (eds), Computational Textile, Springer, Berlin, Heidelberg, pp. 147-165, 2007. https://doi.org/10.1007/978-3-540-70658-8_9

PUBLICATIONS

Articles in international peer-reviewed journals indexed by JCR

Hamad B., Jaafor O., Thomassey S., Hamad M., Bruniaux P., The Semi-supervised Approach for Data Driven and Consumer Oriented Sizing Systems in the Clothing Industry, IEEE Transactions on Engineering Management, 2021, https://doi.org/10.1109/TEM.2021.3104926

He Z., Xu J., Tran K.P., Thomassey S., Zeng X., Yi C., Modeling of textile manufacturing processes using intelligent techniques: a review. International Journal Advanced Manufacturing Technology, 116, 39–67, 2021. https://doi.org/10.1007/s00170-021-07444-1

He Z., Tran K.P., Thomassey S., Zeng X., Xu J., Yi C., Multi-objective optimization of the textile manufacturing process using deep-Q-network based multi-agent reinforcement learning, Journal of Manufacturing Systems, 2021. https://doi.org/10.1016/j.jmsy.2021.03.017.

Xu Y., Thomassey S., Zeng X., Machine learning-based marker length estimation for garment mass customization. International Journal of Advanced Manufacturing Technology, 2021. https://doi.org/10.1007/s00170-021-06833-w

Nguyen H.D., Tran K.P, Thomassey S., Hamad M., Forecasting and Anomaly Detection approaches using LSTM and LSTM Autoencoder techniques with the applications in Supply Chain Management, International Journal of Information Management, Volume 57, 2021. https://doi.org/10.1016/j.ijinfomgt.2020.102282

He Z., Tran K.P., Thomassey S., Zeng X., Xu J., Yi C., A Deep Reinforcement Learning Based Multi-Criteria Decision Support System for Optimizing Textile Chemical Process, Computers in Industry, Volume 125, 2021. https://doi.org/10.1016/j.compind.2020.103373

Xu Y., Thomassey S., Zeng X., Garment mass customization methods for the cutting-related processes. Textile Research Journal. September 2021. https://doi.org/10.1177/0040517520957399

Sirilertsuwan P., Thomassey, S., Zeng, X., A Strategic Location Decision-Making Approach for Multi-Tier Supply Chain Sustainability. Sustainability, Vol. 12, No. 20:8340, 2020. https://doi.org/10.3390/su12208340

Xu Y. , Thomassey S., Zeng X., Optimization of garment sizing and cutting order planning in the context of mass customization. International Journal of Advanced Manufacturing Technology, 2020. https://doi.org/10.1007/s00170-019-04866-w

Craparotta G., Thomassey S., Biolatti A., A siamese neural network application for sales forecasting of new fashion products from images, International Journal of Computational Intelligence Systems, Volume 12, Issue 2, 2019, Pages 1537 – 1546, 2019.  https://doi.org/10.2991/ijcis.d.191122.002

Giri C., Thomassey S., Zeng X., Exploitation of Social Network Data for Forecasting Garment Sales, International Journal of Computational Intelligence Systems, Volume 12, Issue 2, 2019, Pages 1423 – 1435. https://doi.org/10.2991/ijcis.d.191109.001

Benkirane R., Thomassey S., Koehl L., Perwuelz A., A consumer-based textile quality scoring model using multi-criteria decision making. Journal of Engineered Fibers and Fabrics, 2019. https://doi.org/10.1177/1558925019854773

Wagner M., Curteza A., Hong Y., Chen Y. , Thomassey S., Zeng X., A design analysis for eco-fashion style using sensory evaluation tools: Consumer perceptions of product appearance, Journal of Retailing and Consumer Services, Volume 51, Pages 253-262, 2019. https://doi.org/10.1016/j.jretconser.2019.06.005

He Z., , Tran K.-P., Thomassey S., Zeng X., Xu J., Changhai Y., Modeling color fading ozonation of reactive-dyed cotton using the Extreme Learning Machine, Support Vector Regression and Random Forest. Textile Research Journal, 2020, 90(7-8), 896-908. https://doi.org/10.1177/0040517519883059

Ma K., Thomassey S., Zeng X., Wang L., Chen Y., A resource sharing solution optimized by simulation-based heuristic for garment manufacturing, International Journal of Advanced Manufacturing Technology, 2018. https://doi.org/10.1007/s00170-018-2677-3

Ma K., Thomassey S., Zeng X., Development of a Central Order Processing System for Optimizing Demand-Driven Textile Supply Chains: a Real Case Based Simulation Study, Annals of Operations Research, 2018, https://doi.org/10.1007/s10479-018-3000-2

Hamad M., Thomassey S., Bruniaux P., A new sizing system based on 3D shape descriptor for morphology clustering, Computers & Industrial Engineering, Vol. 113, 683-692, 2017, https://doi.org/10.1016/j.cie.2017.05.030

Agrawal T.K., Thomassey S., Cochrane C., Lemort G., Koncar V., Low-Cost Intelligent Carpet System for Footstep Detection, IEEE Sensors Journal, Vol. 17, No. 13, 4239 – 4247, 2017. https://doi.org/10.1109/JSEN.2017.2703633

Brahmadeep, Thomassey S., A simulation based comparison: Manual and automatic distribution setup in a textile yarn rewinding unit of a yarn dyeing factory, Simulation Modelling Practice and Theory, 45, pp. 80-90, 2014. https://doi.org/10.1016/j.simpat.2014.04.002

Thomassey, S.; Bruniaux, P., A template of ease allowance for garments based on a 3D reverse methodology, International Journal of Industrial Ergonomics, 43 (5), 406-416, 2013. https://doi.org/10.1016/j.ergon.2013.08.002

Kursun Bahadir S., Thomassey S., Koncar V., Kalaoglu F., An Algorithm Based on Neuro-Fuzzy Controller Implemented in A Smart Clothing System For Obstacle Avoidance, International Journal of Computational Intelligence Systems, 6 (3), 503-517, 2013. http://dx.doi.org/10.1080/18756891.2013.781336

Rasheed A., Zeng X., Thomassey S., An Approach to the Design of a Fuzzy Logic Model for the Ease Allowance Calculation in Loose Fitting Knee Length Ladies Trousers. Journal of Engineered Fibers and Fabrics, 8 (14), 126-131, 2013.

Kursun Bahadir S., Kalaoglu F, Thomassey S, Cristian I, Koncar V., A study on the beam pattern of ultrasonic sensor integrated to textile structure, International Journal of Clothing Science and Technology, Vol. 23, Number 4, pp. 232-241 (10), 2011. https://doi.org/10.1108/09556221111136494

Kursun-Bahadir S., Koncar V., Kalaoğlu F., Irina C., Thomassey S., Assessing the signal quality of an ultrasonic sensor on different conductive yarns used as transmission lines, Fibres & Textiles in Eastern Europe, 5 (88), 75-81, 2011.

Thomassey S., Sales forecasts in clothing industry: The key success factor of the supply chain management, International Journal of Production Economics, Volume 128, pp 470-483, 2010. https://doi.org/10.1016/j.ijpe.2010.07.018

Thomassey, S., Happiette, M., A neural clustering and classification system for sales forecasting of new apparel items, Applied Soft Computing, special issue Soft Computing for time series prediction, Volume 7, Issue 4, pp. 1177-1187, 2007. https://doi.org/10.1016/j.asoc.2006.01.005

Thomassey, S., Fiordaliso, A., A hybrid forecasting method based on clustering and decision trees, Decision Support Systems, vol. 42, pp. 408-421, 2006. https://doi.org/10.1016/j.dss.2005.01.008

Thomassey, S., Happiette, M., Castelain, J.M., A global forecasting support system adapted to textile distribution, International Journal of Production Economics, vol. 96/1, pp 81-95, 2005. https://doi.org/10.1016/j.ijpe.2004.03.001

Thomassey, S., Happiette, M., Castelain, J.M., A short and mid-term automatic forecasting system – Application to textile logistics, European Journal of Operational Research, Special issue: IEPM, Focus on Scheduling, vol. 161/1, pp 275-284, 2005. https://doi.org/10.1016/j.ejor.2002.09.001

Thomassey, S., Happiette, M., Castelain, J.M., Mean-term textile sales forecasting using families and items classification, Studies in Informatics and Control, mars 2003, vol. 12, n°1, pp. 41-52, 2003.

Thomassey, S., Happiette, M., Dewaele, N., Castelain, J.M., A short and mean-term forecasting system adapted to textile items sales, Journal of the Textile Institute, vol. 93, pp. 95-104, 2002. https://doi.org/10.1080/00405000208658360

Thomassey, S., Vroman, P., Happiette, M., Castelain, J.M., A Comparative Test of New Mean-Term Forecasting Models Adapted to Textile Items Sales, Studies in Informatics and Control, vol. 10, no. 3, pp. 209-225, 2001.

Articles in international peer-reviewed journals not indexed by JCR

Sirilertsuwan P., Thomassey S., Zeng X., Chen Y., How Living Wages Influence Apparel Costs and Comparative Advantages among Different Multi-tier Supply Chains, Journal of Fiber Bioengineering and Informatics 15:1, 2022, 1-15. doi:10.3993/jfbim00377

Wagner M., A. Curteza, S. Thomassey, X. Zeng. The Appearance of Sustainable Fashion Products. Current Trends in Fashion Technology and Textile Engineering, 2(5), 2018. https://doi.org/10.19080/CTFTTE.2018.02.555599

Hamad B., Hamad M., Thomassey S. et Bruniaux P., 3D Adaptive Morphotype Mannequin for Target Population, Journal of Ergonomics, 8 :2, 2018. https://doi.org/10.4172/2165-7556.1000229

Wagner M, Chen Y, Curteza A, Thomassey S, Perwuelz A, et Zeng X., (2017) Fashion Product Solutions and Challenges for Environmental and Trend Conscious Consumers. Journal of Fashion Technology and Textile Engineering S3:010. https://doi.org/10.4172/2329-9568.S3-010

Agrawal T.K., Thomassey S., Cochrane C., Koncar V., Data Analysis and Statistical Interpolation of Signals for Human Footstep Tracking Using Intelligent Carpet. Journal of Fashion Technology and Textile Engineering, 2016. https://doi.org/10.4172/2329-9568.S2-007

Thomassey, S., Happiette, M., Castelain, J.M., An automatic textile sales forecast using fuzzy treatment of explanatory variables, Journal of Textile and Apparel, Technology and Management JTAM, vol. 2, issue 4, pp. 1-15, 2002.

Thomassey, S., Happiette, M., Castelain, J.M., Modèle de prévision des ventes à moyen terme avec traitement flou des variables explicatives – Application à la logistique textile, Journal Européen des Systèmes Automatisés (JESA), vol. 36, no.8, 2002, pp. 1051-1078, 2002.

TEACHING

  • Production management
  • Supply chain management

AWARDS

  • 2021 : The top 25 most cited for International Journal of Information Management in 2021 (IF 2021 = 18.958):

Nguyen H.D., Tran K.P, Thomassey S., Hamad M., Forecasting and Anomaly Detection approaches using LSTM and LSTM Autoencoder techniques with the applications in Supply Chain Management, International Journal of Information Management, Volume 57, 2021. https://doi.org/10.1016/j.ijinfomgt.2020.102282