Michael Kokkolaras

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Cahiers du GERAD

22 results — page 1 of 2

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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...

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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 COVID-19 is known to be highly dependent on individual viral dynamics. Since the cycle threshold (Ct) is the only semi-qua...

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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...

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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...

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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...

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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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