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Heuristics for Optimization and Learning

Farouk Yalaoui 1 Lionel Amodeo 1 El-Ghazali Talbi 2, 3 
1 LOSI - Laboratoire d'Optimisation des Systèmes Industriels
LIST3N - Laboratoire Informatique et Société Numérique
2 BONUS - Optimisation de grande taille et calcul large échelle
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
Abstract : This book is a new contribution aiming to give some last research findings in the field of optimization and computing. This work is in the same field target than our two previous books published: “Recent Developments in Metaheuristics” and “Metaheuristics for Production Systems”, books in Springer Series in Operations Research/Computer Science Interfaces. The challenge with this work is to gather the main contribution in three fields, optimization technique for production decision, general development for optimization and computing method and wider spread applications. The number of researches dealing with decision maker tool and optimization method grows very quickly these last years and in a large number of fields. We may be able to read nice and worthy works from research developed in chemical, mechanical, computing, automotive and many other fields.
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Submitted on : Tuesday, June 15, 2021 - 1:05:40 PM
Last modification on : Sunday, June 26, 2022 - 9:27:00 AM



Farouk Yalaoui, Lionel Amodeo, El-Ghazali Talbi. Heuristics for Optimization and Learning. 906, Springer, 2021, Studies in Computational Intelligence (SCI), 978-3-030-58932-5. ⟨10.1007/978-3-030-58930-1⟩. ⟨hal-03261026⟩



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