Optimization of Uncertainty Features for Transportation Problems
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This presentation discusses real-time optimization (RTO) strategies for improving process performance in the presence of uncertainty in the form of plant-model mismatch, drifts and disturbances. RTO typically uses a plant model to compute optimal inputs. I ...
The objective of this thesis is to develop reduced models for the numerical solution of optimal control, shape optimization and inverse problems. In all these cases suitable functionals of state variables have to be minimized. State variables are solutions ...
Current superstructure size for energy system design is increasing with computing facility improvement. Despite such approach allows to link and to analyse a lot of elements, demonstrating the advantage of a global optimization, non-negligible uncertaintie ...
This work presents a synthesis method that leads to the preliminary design of industrial energy systems. Such systems are composed of several technologies that transform, through a set of physical unit operations, raw materials and energy into products and ...
In this paper, we present an application to the Airline Scheduling Problem (ASP) of the Uncertainty Feature Optimization (UFO) framework which combines both a proactive scheduling algorithm and a reactive recovery algorithm used for re-optimization when di ...
This presentation discusses real-time optimization (RTO) strategies for improving process performance in the presence of uncertainty in the form of plant-model mismatch, drifts and disturbances. RTO typically uses a plant model to compute optimal inputs. I ...
Challenges in real-time process optimization mainly arise from the inability to build and adapt accurate models for complex physico-chemical processes. This paper surveys different ways of using measurements to compensate for model uncertainty in the conte ...
The paper presents an optimization design of an in-wheel BLDC motor for a kick scooter. The optimization is performed using a genetic optimization tool combined with a FEM commercial software. The new contributions of the paper are: (i) introduction of thr ...
This thesis deals with models and methods for large scale optimization problems; in particular, we focus on decision problems arising in the context of seaport container terminals for the efficient management of terminal operations. Large-scale optimizatio ...
Optimization problems due to noisy data solved using stochastic programming or robust optimization approaches require the explicit characterization of an uncertainty set U that models the nature of the noise. Such approaches depend on the modeling of the u ...