Michael Kokkolaras
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Cahiers du GERAD
A challenge in aircraft design optimization is the presence of non-computable, so-called hidden, constraints that do not return a value in certain regions of...
référence BibTeXRisk averse constrained blackbox optimization under mixed aleatory/epistemic uncertainties
This paper addresses risk averse constrained optimization problems where the objective and constraint functions can only be computed by a blackbox subject to...
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This work considers stochastic optimization problems in which the objective function values can only be computed by a blackbox corrupted by some random noise...
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The transmission of the contagious Coronavirus disease (COVID-19) is highly dependent on individual viral dynamics. Reverse-transcription quantitative polyme...
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Engineering design is often faced with uncertainties, making it difficult to determine an optimal design. In an unconstrained context, this amounts to choose...
référence BibTeXOptimization of infectious disease prevention and control policies using agent-based modeling
The spread of an infectious disease such as COVID-19 is governed by complex social interactions that are challenging to model. Policy makers must take measur...
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We consider computationally expensive blackbox optimization problems and present a method that employs surrogate models and concurrent computing at the searc...
référence BibTeXConstrained stochastic blackbox optimization using a progressive barrier and probabilistic estimates
This work introduces the StoMADS-PB algorithm for constrained stochastic blackbox optimization, which is an extension of the mesh adaptive direct-search (MAD...
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This work reviews blackbox optimization applications over the last twenty years, addressed using direct search optimization methods. Emphasis is placed on...
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Nanoparticle-mediated drug delivery may be a promising alternative to traditional chemo-therapy of high systemic toxicity. Tumor tissue architecture poses a ...
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This work introduces StoMADS, a stochastic variant of the mesh adaptive direct-search (MADS) algorithm originally developed for deterministic blackbox optim...
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In the interest of full disclosure, the reader is advised that I am biased positively towards the book considered here as I have collaborated with its first ...
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Nanotherapy represents a promising approach to target tumors with anticancer drugs while minimizing systemic toxicity. Evaluation of nanoparticle (NP) design...
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We investigate surrogate-assisted strategies for global derivative-free optimization using the mesh adaptive direct search MADS blackbox optimization algorit...
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The particularities of the aircraft parts riveting process simulation necessitate the solution of a large amount of contact problems. We propose a primal-dua...
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Nanoparticle-based drug delivery is a promising method to increase the therapeutic index of anti-cancer agents with low median toxic dose. The delivery effic...
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Locally weighted regression combines the advantages of polynomial regression and kernel smoothing. We present three ideas for appropriate and effective use...
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This paper presents a numerical investigation of the non-hierarchical formulation of Analytical Target Cascading (ATC) for coordinating distributed multidisc...
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Various constrained problem formulations for the optimization of an electro-thermal wing anti-icing system in both running-wet and evaporative regimes are pr...
référence BibTeXSystem-of-systems approach to air transportation design using nested optimization and direct search
Aircraft sizing, route network design, demand estimation and allocation of aircraft to routes are different facets of the air transportation optimization pro...
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Typical challenges of simulation-based design optimization include unavailable gradients and unreliable approximations thereof, expensive function evaluation...
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In the literature, thermal insulation systems with a fixed number of heat intercepts have been optimized with respect to intercept locations and temperature...
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