Majid Soleimani-Damaneh

dblp:92/3896 · DBLP profile ↗
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11ranked-venue papers
4as first author
4since 2021 · last 2026
0000-0002-5913-1035ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 7 · 1 first-author · 3 since 2021Artificial intelligence and machine learning · 4 · 3 first-author · 1 since 2021
YearPublicationVenuePosition
2026 Joint sample-feature subspace learning via bidirectional reconstruction for feature selection
Morteza Maleknia, Farid Saberi Movahed, Majid Soleimani-Damaneh
Neurocomputing3
2024 A new dual-based cutting plane algorithm for nonlinear adjustable robust optimization
Abbas Khademi, Ahmadreza Marandi, Majid Soleimani-Damaneh
J. Glob. Optim.3
2023 Aubin property for solution set in multi-objective programming
Morteza Rahimi 0001, Majid Soleimani-Damaneh
J. Glob. Optim.2
2022 LR-NIMBUS: an interactive algorithm for uncertain multiobjective optimization with lightly robust efficient solutions
Javad Koushki, Kaisa Miettinen, Majid Soleimani-Damaneh
J. Glob. Optim.3
2020 Characterization of the weakly efficient solutions in nonsmooth quasiconvex multiobjective optimization
Nader Kanzi, Majid Soleimani-Damaneh
J. Glob. Optim.2
2020 Characterization of generalized FJ and KKT conditions in nonsmooth nonconvex optimization
Javad Koushki, Majid Soleimani-Damaneh
J. Glob. Optim.2
2018 Hartley properly and super nondominated solutions in vector optimization with a variable ordering structure
Shokouh Shahbeyk, Majid Soleimani-Damaneh, Refail Kasimbeyli
J. Glob. Optim.2
2012 Duality for optimization problems in Banach algebras
Majid Soleimani-Damaneh
J. Glob. Optim.1
2010 Returns to scale and scale elasticity in the presence of weight restrictions and alternative solutions
Majid Soleimani-Damaneh, Gholam Reza Jahanshahloo, S. Mehrabian, Maryam Hasannasab
Knowl. Based Syst.1
2009 Shannon's entropy for combining the efficiency results of different DEA models: Method and application
Majid Soleimani-Damaneh, Masoud Zarepisheh
Expert Syst. Appl.1
2008 Modified big-M method to recognize the infeasibility of linear programming models
abstract
This paper provides an effective modification to the big-M method which leads to reducing the iterations of this method, when it is used to recognize the infeasibility of linear systems.
Majid Soleimani-Damaneh
Knowl. Based Syst.1