A queue-based aggregation approach for performance evaluation of a production system with an AMHS. - Mehrdad Mohammadi; Stéphane Dauzère-Pérès; Claude Yugma; Maryam Karimi Mamaghan (Comput. Oper. Res., 2020)

A learning-based metaheuristic for a multi-objective agile inspection planning model under uncertainty. - Maryam Karimi Mamaghan; Mehrdad Mohammadi; Payman Jula; Amir Pirayesh; Hadi Ahmadi (Eur. J. Oper. Res., 2020)

A possibilistic closed-loop supply chain: pricing, advertising and remanufacturing optimization. - Ata Allah Taleizadeh; Maryam Karimi Mamaghan; Seyed Ali Torabi (Neural Comput. Appl., 2020)

A Learning-Based Iterated Local Search Algorithm for Solving the Traveling Salesman Problem. - Maryam Karimi Mamaghan; Bastien Pasdeloup; Mehrdad Mohammadi; Patrick Meyer (OLA, 2021)

Capacitated location routing problem with simultaneous pickup and delivery under the risk of disruption. - Milad Dehghan; Seyed Reza Hejazi; Maryam Karimi Mamaghan; Mehrdad Mohammadi; Amir Pirayesh (RAIRO Oper. Res., 2021)

Machine learning at the service of meta-heuristics for solving combinatorial optimization problems: A state-of-the-art. - Maryam Karimi Mamaghan; Mehrdad Mohammadi; Patrick Meyer; Amir Mohammad Karimi-Mamaghan; El-Ghazali Talbi (Eur. J. Oper. Res., 2022)

Hybridizing metaheuristics with machine learning for combinatorial optimization : a taxonomy and learning to select operators. (Hybridation des métaheuristiques avec l'apprentissage automatique pour l'optimisation combinatoire : une taxonomie et apprendre à sélectionner des opérateurs). - Maryam Karimi Mamaghan (2022)

Learning to select operators in meta-heuristics: An integration of Q-learning into the iterated greedy algorithm for the permutation flowshop scheduling problem. - Maryam Karimi Mamaghan; Mehrdad Mohammadi; Bastien Pasdeloup; Patrick Meyer (Eur. J. Oper. Res., 2023)

Dynamic operator management in meta-heuristics using reinforcement learning: an application to permutation flowshop scheduling problems. - Maryam Karimi Mamaghan; Mehrdad Mohammadi; Wout Dullaert; Daniele Vigo; Amir Pirayesh (CoRR, 2024)