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In this course, we will focus on problems relevant to Operations Research where several conflicting objectives have to be minimized to compute a solution. First the basics of multiobjective optimization will be introduced (Pareto optimality, properties on the Pareto front, complexity results) in order for the students to fully capture the important notions. We will notably focus on problems which can be modeled by means of mixed integer linear programming. Second, the different methods for computing Pareto optima will be introduced sketching by the way their main properties, advantages and drawbacks. Third, we will take numerous examples from multicriteria scheduling theory to illustrate how in practice multiobjective optimization problems can be solved. This will be the opportunity to present various multiobjective scheduling models from classic ones to more complex ones. For each of them, heuristic and exact optimization algorithms will be presented. This content will follow my milestone book on multicriteria scheduling • V. T’KINDT, J.-C. BILLAUT. Multicriteria Scheduling: Theory, Models and Algorithms, Springer, 2nd edition, 2006.

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Presentazione report scritto

P.D.2-2 - Settembre

Classroom B (DIGEP) 1. 21/09/2021 : 9h-11h 2. 22/09/2021 : 9h-11h 3. 28/09/2021 : 9h-11h 4. 29/09/2021 : 9h-11h 5. 5/10/2021 : 9h-11h 6. 6/10/2021 : 9h-11h 7. 12/10/2021 : 9h-11h 8. 13/10/2021 : 9h-11h 9. 19/10/2021 : 9h-11h 10. 20/10/2021 : 9h-11h