Publication

Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization

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We present a computational inverse design method for a new class of surface-based inflatable structure. Our deployable structures are fabricated by fusing together two layers of inextensible sheet material along carefully selected curves. The fusing curves ...

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Geometric optimization of dielectric elastomer electrodes for dynamic applications

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Dielectric elastomers are soft actuators, made of an elastomer membrane sandwiched by compliant electrodes. Because of their high energy density and quick response, they are well suited for dynamic applications such as loudspeakers. Thanks to progress in t ...

ELSEVIER SCI LTD2021

Optimization Methods for Control: From Embedded Programmable Hardware to Data-Driven Process Optimization

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The research community has been making significant progress in hardware implementation, numerical computing and algorithm development for optimization-based control. However, there are two key challenges that still have to be overcome for optimization-base ...

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Automated switch-block exploration gains in importance as technology scaling brings more emphasis on the physical constraints, making it insufficient to rely on abstract measures of routability alone. In this work, we take an approach that significantly di ...

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Increasing Superstructure Optimization Capacity Through Self-Learning Surrogate Models

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Simulation-based optimization models are widely applied to find optimal operating conditions of processes. Often, computational challenges arise from model complexity, making the generation of reliable design solutions difficult. We propose an algorithm fo ...

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Pareto-like sequential sampling heuristic for global optimisation

Katrin Beyer, Mahmoud S. M. Shaqfa

In this paper, we propose a simple global optimisation algorithm inspired by Pareto’s principle. This algorithm samples most of its solutions within prominent search domains and is equipped with a self-adaptive mechanism to control the dynamic tightening o ...

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Simultaneous Perturbation Stochastic Approximation of the Quantum Fisher Information

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The Quantum Fisher Information matrix (QFIM) is a central metric in promising algorithms, such as Quantum Natural Gradient Descent and Variational Quantum Imaginary Time Evolution. Computing the full QFIM for a model with d parameters, however, is computat ...

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Systematic Method for the Energy-Saving Potential Calculation of Air Conditioning Systems via Data Mining. Part II: A Detailed Case Study

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Increased data monitoring enables the energy-efficient operation of air-conditioning systems via data-mining. The latter is projected to have lesser consumption but more comprehensive diagnosis than traditional methods. Following the companion paper that p ...

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