Karim Tamssaouet

Postdoktorstipendiat - Institutt for regnskap, revisjon og foretaksøkonomi


Karim Tamssaouet is an Assistant Professor at BI Norwegian Business School. He received his Ph.D. from École des Mines de Saint-Étienne. He is interested in designing efficient and effective solution approaches that solve real-life optimization problems. His current research revolves around scheduling and integrated inventory–transportation problems. He is currently teaching courses on Mathematical Programming and Inventory Management.


Tamssaouet, Karim; Dauzère-Pérès, Stéphane, Knopp, Sebastian, Bitar, Abdoul & Yugma, Claude (2022)

Multiobjective Optimization for Complex Flexible Job-Shop Scheduling Problems

European Journal of Operational Research, 296(1), s. 87- 100. Doi: 10.1016/j.ejor.2021.03.069

In this paper, we are concerned with the resolution of a multiobjective complex job-shop scheduling problem stemming from semiconductor manufacturing. To produce feasible and industrially meaningful schedules, this paper extends the recently proposed batch-oblivious approach by considering unavailability periods and minimum time lags and by simultaneously optimizing multiple criteria that are relevant in the industrial context. A novel criterion on the satisfaction of production targets decided at a higher level is also proposed. Because the solution approach must be embedded in a real-time application, decision makers must express their preferences before the optimization phase. In addition, a preference model is introduced where trade-off is only allowed between some criteria. Two a priori multiobjective extensions of Simulated Annealing are proposed, which differ in how the simultaneous use of a lexicographic order and weights is handled when evaluating the fitness. A known a posteriori approach of the literature is used as a benchmark. All the metaheuristics are embedded in a Greedy Randomized Adaptive Search Procedure. The different versions of the archived GRASP approach are compared using large industrial instances. The numerical results show that the proposed approach provides good solutions regarding the preferences. Finally, the comparison of the optimized schedules with the actual factory schedules shows the significant improvements that our approach can bring.

Le Quéré, Étienne; Dauzère-Pérès, Stéphane, Tamssaouet, Karim, Maufront, Cédric & Astie, Stéphane (2020)

Dynamic Sampling for Risk Minimization in Semiconductor Manufacturing

Winter simulation conference : proceedings Doi: 10.1109/WSC48552.2020.9384001

Tamssaouet, Karim; Dauzère-Pérès, Stéphane, Yugma, Claude, Knopp, Sebastian & Pinaton, Jacques (2018)

A Study on the Integration of Complex Machines in Complex Job Shop Scheduling

Winter simulation conference : proceedings

Tamssaouet, Karim; Dauzère-Pérès, Stéphane & Yugma, Claude (2018)

Metaheuristics for the job-shop scheduling problem with machine availability constraints

Computers & industrial engineering Doi: 10.1016/j.cie.2018.08.008

Tamssaouet, Karim; Dauzère-Pérès, Stéphane & Yugma, Claude (2018)

Minimizing makespan on parallel batch processing machines

[Academic lecture]. International Conference on Project Management and Scheduling.

Tamssaouet, Karim; Dauzère-Pérès, Stéphane, Yugma, Claude & Pinaton, Jacques (2017)

A Batch-oblivious Approach For Scheduling Complex Job-Shops with Batching Machines: From Non-delay to Active Scheduling

[Academic lecture]. Multidisciplinary International Conference on Scheduling: Theory and Applications.

Akademisk grad
År Akademisk institusjon Grad
2019 École des Mines de Saint-Étienne PhD
2015 Université Paris Dauphine Master of Management
2014 Ecole Nationale Polytechnique Other
År Arbeidsgiver Tittel
2020 - Present BI Norwegian Business School Assistant Professor
2019 - 2020 Ecole Des Mines de Saint Etienne Postdoctoral Researcher
2016 - 2019 STMicroelectronics Research & Development Engineer