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Ansattprofil

Karim Tamssaouet

Postdoktorstipendiat - Institutt for regnskap, revisjon og foretaksøkonomi

Biografi

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 Business Optimization and Supply Chain Analytics.

Publikasjoner

Tamssaouet, Karim; Engebrethsen, Erna & Dauzère-Pérès, Stéphane (2023)

Multi-item dynamic lot sizing with multiple transportation modes and item fragmentation

International Journal of Production Economics, 265, s. 1- 15. Doi: 10.1016/j.ijpe.2023.109001 - Fulltekst i vitenarkiv

This paper addresses a tactical joint inventory and transportation planning problem for multiple items with deterministic and time-varying demand, considering different transportation modes and item fragmentation. The latter corresponds to the splitting of the same item ordered quantity between several trucks or containers. On the one hand, fragmenting the items potentially reduces the number of containers used. On the other hand, loading the item lot fragments on several containers may negatively impact the handling and shipping operations. This new problem is proposed as a way to tackle such conflict. Several Mixed Integer Linear Programming models are proposed for the problem, which rely on two multi-item lot-sizing models with mode selection and two bin-packing models with item fragmentation. A relax-and-fix heuristic is also proposed. Using realistic instances, computational experiments are first conducted to identify the most efficient model in terms of computational time, to study the impact of key parameters on the computational complexity and to analyze the efficiency of the heuristic. Then, managerial insights are derived through additional computational experiments, in particular, to identify contexts requiring joint optimization of lot-sizing and bin-packing decisions, as well as the impact of item fragmentation constraints. Directions for future research are finally proposed.

Dauzère-Pérès, Stéphane; Ding, Junwen, Shen, Liji & Tamssaouet, Karim (2023)

The flexible job shop scheduling problem: A review

European Journal of Operational Research Doi: 10.1016/j.ejor.2023.05.017

The flexible job shop scheduling problem (FJSP) is an NP-hard combinatorial optimization problem, which has wide applications in the real world. The complexity and relevance of the FJSP have led to numerous research works on its modeling and resolution. This paper reviews some of the research of the past 30 years on the problem, by presenting and classifying the different criteria, constraints, configurations and solution approaches that have been considered. Recent emerging topics on complex shop scheduling, multi-criteria optimization and uncertain and dynamic environments are discussed. Finally, future research opportunities are proposed.

Tamssaouet, Karim & Dauzère-Pérès, Stéphane (2023)

A general efficient neighborhood structure framework for the job-shop and flexible job-shop scheduling problems

European Journal of Operational Research, 311(2), s. 455- 471. Doi: 10.1016/j.ejor.2023.05.018 - Fulltekst i vitenarkiv

This article introduces a framework that unifies and generalizes well-known literature results related to local search for the job-shop and flexible job-shop scheduling problems. In addition to the choice of the metaheuristic and the neighborhood structure, the success of most of the influential local search approaches relies on the ability to quickly and efficiently rule out infeasible moves and evaluate the quality of the feasible neighbors. Hence, the proposed framework focuses on the feasibility and quality evaluation of a general move when solving the job-shop and flexible job-shop scheduling problems for any regular objective function. The proposed framework is valid for any scheduling problem where the defined neighborhood structure is appropriate, and each solution to the problem can be modeled with a directed acyclic graph with {non-negative weights on nodes and arcs}. The feasibility conditions and quality estimation procedures proposed in the literature rely heavily on information on the existence of a path between two nodes. Thus, based on an original parameterized algorithm that asserts the existence of a path between two nodes, novel generic procedures to evaluate the feasibility of a move and estimate the value of any regular objective function of a neighbor solution are proposed. We show that many well-known literature results are special cases of our results, which can be applied to a wide range of shop scheduling problems.

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 - Fulltekst i vitenarkiv

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; Engebrethsen, Erna & Dauzère-Pérès, Stéphane (2023)

Multi-item dynamic lot sizing with multiple transportation modes and item fragmentation

[Academic lecture]. Finnish Operations Research Society.

Tamssaouet, Karim & Dauzère-Pérès, Stéphane (2022)

Towards a General Local Search Framework for Job-shop Scheduling Problems

[Academic lecture]. NORS Annual Conference 2022.

Tamssaouet, Karim; Engebrethsen, Erna & Dauzère-Pérès, Stéphane (2022)

Multi-item dynamic lot sizing with multiple transportation modes and item fragmentation

[Academic lecture]. International Workshop on Lot Sizing (IWLS 2022).

Flygansvær, Bente Merete; Laari, Sini, Mikkelsen, Ole Stegmann, Tamssaouet, Karim, Gillström, Henrik & Stefánsson, Gunnar (2021)

Book of Abstracts - The 33rd Annual NOFOMA Conference

[Report]. Nordic Logistics Research Network.

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
Arbeidserfaring
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