2024

Heure:	10:30 - 11:00
Lieu:	Salle B107, bâtiment B, Université de Villetaneuse
Résumé:	Online policy selection for inventory problems
Description:	Adeline Fermanian After a general presentation of the company Califrais and of research problems arising in food supply chain, we will focus on a recent work on online inventory problems. These are decision problems where at each time period the manager has to make a replenishment decision based on partial historical information in order to meet demands and minimize costs. To solve such problems, we build upon recent works in online learning and control, use insights from inventory theory and propose a new algorithm called GAPSI. This algorithm follows a new feature-enhanced base-stock policy and deals with the troublesome question of non-differentiability which occurs in inventory problems. Our method is illustrated in the context of a complex and novel inventory system involving multiple products, lost sales, perishability, warehouse-capacity constraints and lead times. Extensive numerical simulations are conducted to demonstrate the good performances of our algorithm on real-world data.

Heure:	10:30 - 11:30
Lieu:	Salle B107, bâtiment B, Université de Villetaneuse
Résumé:	New perspectives on invexity and its algorithmic applications
Description:	Ksenia Bestuzheva One of the key properties of convex problems is that every stationary point is a global optimum, and nonlinear programming algorithms that converge to local optima are thus guaranteed to find the global optimum. However, some nonconvex problems possess the same property. This observation has motivated research into generalizations of convexity. This talk proposes a new generalization which we refer to as optima-invexity: the property that only one connected set of optimal solutions exists. We state conditions for optima-invexity of unconstrained problems and discuss structures that are promising for practical use, and outline algorithmic applications of these structures.