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Mustapha Nourelfath
Mustapha Nourelfath
Verified email at gmc.ulaval.ca
Title
Cited by
Cited by
Year
Tabu search for the redundancy allocation problem of homogenous series–parallel multi-state systems
M Ouzineb, M Nourelfath, M Gendreau
Reliability Engineering & System Safety 93 (8), 1257-1272, 2008
2092008
A multi-stage stochastic programming approach for production planning with uncertainty in the quality of raw materials and demand
M Kazemi Zanjani, M Nourelfath, D Ait-Kadi
International Journal of Production Research 48 (16), 4701-4723, 2010
1942010
Performance evaluation of multi-state degraded systems with minimal repairs and imperfect preventive maintenance
IW Soro, M Nourelfath, D Aït-Kadi
Reliability Engineering & System Safety 95 (2), 65-69, 2010
1942010
Integrated preventive maintenance and production decisions for imperfect processes
M Nourelfath, N Nahas, M Ben-Daya
Reliability engineering & system safety 148, 21-31, 2016
1862016
Robust production planning in a manufacturing environment with random yield: A case in sawmill production planning
MK Zanjani, D Ait-Kadi, M Nourelfath
European Journal of Operational Research 201 (3), 882-891, 2010
1762010
Integrating noncyclical preventive maintenance scheduling and production planning for a single machine
MC Fitouhi, M Nourelfath
International journal of production economics 136 (2), 344-351, 2012
1732012
Integrating noncyclical preventive maintenance scheduling and production planning for multi-state systems
MC Fitouhi, M Nourelfath
Reliability Engineering & System Safety 121, 175-186, 2014
1562014
An integrated model for production and preventive maintenance planning in multi-state systems
M Nourelfath, MC Fitouhi, M Machani
IEEE Transactions on Reliability 59 (3), 496-506, 2010
1552010
Ant system for reliability optimization of a series system with multiple-choice and budget constraints
N Nahas, M Nourelfath
Reliability Engineering & System Safety 87 (1), 1-12, 2005
1522005
Coupling ant colony and the degraded ceiling algorithm for the redundancy allocation problem of series–parallel systems
N Nahas, M Nourelfath, D Ait-Kadi
Reliability Engineering & System Safety 92 (2), 211-222, 2007
1322007
Integrating production, inventory and maintenance planning for a parallel system with dependent components
M Nourelfath, E Châtelet
Reliability Engineering & System Safety 101, 59-66, 2012
1292012
A new approach for buffer allocation in unreliable production lines
N Nahas, D Ait-Kadi, M Nourelfath
International journal of production economics 103 (2), 873-881, 2006
1242006
Optimization of series–parallel multi-state systems under maintenance policies
M Nourelfath, D Ait-Kadi
Reliability Engineering & System Safety 92 (12), 1620-1626, 2007
1082007
Joint redundancy and imperfect preventive maintenance optimization for series–parallel multi-state degraded systems
M Nourelfath, E Châtelet, N Nahas
Reliability Engineering & System Safety 103, 51-60, 2012
962012
A cost minimisation model for joint production and maintenance planning under quality constraints
H Beheshti Fakher, M Nourelfath, M Gendreau
International Journal of Production Research 55 (8), 2163-2176, 2017
822017
Availability of K-out-of-N: G systems with non-identical components subject to repair priorities
A Khatab, N Nahas, M Nourelfath
Reliability Engineering & System Safety 94 (2), 142-151, 2009
762009
Integrating production, maintenance and quality: A multi-period multi-product profit-maximization model
HB Fakher, M Nourelfath, M Gendreau
Reliability Engineering & System Safety 170, 191-201, 2018
732018
Six Sigma performance for non-normal processes
T Aldowaisan, M Nourelfath, J Hassan
European Journal of Operational Research 247 (3), 968-977, 2015
682015
A multi-agent approach for integrated emergency vehicle dispatching and covering problem
S Ibri, M Nourelfath, H Drias
Engineering Applications of Artificial Intelligence 25 (3), 554-565, 2012
682012
A deep learning predictive model for selective maintenance optimization
H Hesabi, M Nourelfath, A Hajji
Reliability Engineering & System Safety 219, 108191, 2022
672022
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