Journées communes DOR/REST

Optimization under uncertainty in energy planning
Wim van Ackooij (chercheur, EDF)

In this talk we will discuss several aspects of energy planning and how optimizing under uncertainty fits into the picture. We will also highlight some specifically applied approaches and discuss some techical points.

Autour de l'optimisation robuste dans les réseaux 
Walid Ben Ameur (professeur, Telecom SudParis)

L'optimisation robuste propose un cadre adéquat pour définir des solutions pouvant s'adapter aux incertitudes dans les réseaux de communication. Je tenterais d'exposer une partie des travaux réalisés dans la communauté pendant les 2 dernières décennies autour du routage robuste dans les réseaux de communication. Je parcourrais les principaux modèles, algorithmes et résultats d'approximation. Naturellement, je développerais plus les travaux auxquels j'ai moi même participé avec différents collègues dont Hervé Kerivin, Mateusz Zotkiewicz, Adam Ouorou, Guanglei Wang, Jérémie Leguay et Yacine Al-Najjar.​​

Appointment scheduling and real-time sequencing strategies for patient unpunctuality 
Xiaolan Xie (professeur, Ecole des Mines de Saint Etienne)

Patient unpunctuality causes perturbations in healthcare operations, compromising productivity and service quality. In this talk, we present various approaches to mitigate the negative impacts of unpunctuality using both appointment scheduling and real-time sequencing taking into account patient unpunctuality, no-shows, random service durations, and multiple providers. The objective is to minimize the total cost incurred by patient waiting and provider overtime. In particular, we will show how stochastic programming, Bender decomposition, stochastic approximation and sample path gradients can be used to design efficient appointment schedules and real time control strategies.

Robust Power Systems Planning under Operational Uncertainties
Adam Abdin (maitre de conférences, CentraleSupelec)

Modern power systems are increasingly subjected to significant net-load uncertainties to which they need to effectively respond to ensure the security of power supply. Those uncertainties are due, among others, to changing user patterns driven by smart-devices, the increase of renewable energy production and the expected prevalence of electric vehicles with vehicle-to-grid capabilities and new charging patterns. Moreover, the dependence of short-term power systems operation on gas availabilities, extreme weather events such as droughts, heatwaves and extreme temperature variations add to the uncertain factors under which power systems must ensure the continuation of supply. In this landscape, accounting for short-term uncertainties in long-term optimal planning models became and essential motivation for the development and usage of suitable robust models capable of dealing with these problems

This presentation illustrates the development of a multistage adaptive robust power system expansion planning model, which accounts for short-term operational constraints and maintains key representation of generation units. The uncertainty of electricity demand and power supply is taken into account in a robust optimization framework with parameters that permit control over the level of conservatism of the solution. An efficient solution method for the resulting multi-stage robust counterpart is also discussed. Moreover, the presentation illustrates how the multistage robust optimization model allows the sequential representation of uncertainty realization as they are revealed over time. It also guarantees the non-anticaptivity of future uncertainty realizations at the time of decision-making, which is a critical consideration in practical real-world applications.

Dealing with uncertainty in air cargo transportation
Bernardo Pagnoncelli (professeur, SKEMA Business School)

Air cargo transportation has been growing steadily in the last decade, and it is responsible for 35% of global trade by value. As with other modes of transportation, several sources of uncertainty affect key decisions such as contracts and routing.
We are going to present two models in air cargo transportation that deal with different sources of uncertainty. We will discuss some modeling choices and present algorithms to solve these problems,
discussing managerial implications of the solutions that are specific to air cargo transportation (Joint work with Felipe Delgado, Masato Wada, and Ricardo Trincado from PUC, Chile).