Publications related to Particle swarm optimization

Cellulan World: Interactive Platform to Learn Swarm Behaviors

Pierre Dillenbourg, Barbara Bruno, Hala Khodr, Aditi Kothiyal

Swarming behaviors are ubiquitous in nature, and an important topic to teach and learn. In the learning sciences domain of complex systems understanding, studies have shown that novices tend to assume that centralized control and leadership should exist wh ...

IFAAMAS2022

UNDERGRAD: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees

Volkan Cevher, Kimon Antonakopoulos

Universal methods for optimization are designed to achieve theoretically optimal convergence rates without any prior knowledge of the problem’s regularity parameters or the accurarcy of the gradient oracle employed by the optimizer. In this regard, existin ...

2022

Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

Colin Neil Jones, Yuning Jiang, Xinliang Dai

The increasing application of voltage source converter (VSC) based high voltage direct current (VSC-HVDC) technology in power grids has raised the importance of incorporating DC grids and converters into the existing transmission network. This poses signif ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Finding symmetry breaking order parameters with Euclidean neural networks

Mario Geiger

Curie's principle states that "when effects show certain asymmetry, this asymmetry must be found in the causes that gave rise to them." We demonstrate that symmetry equivariant neural networks uphold Curie's principle and can be used to articulate many sym ...

AMER PHYSICAL SOC2021

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

Shen Yang, Xianlin Wang

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 ...

MDPI2021

Multikernel Regression with Sparsity Constraint

Michaël Unser, Shayan Aziznejad

In this paper, we provide a Banach-space formulation of supervised learning with generalized total-variation (gTV) regularization. We identify the class of kernel functions that are admissible in this framework. Then, we propose a variation of supervised l ...

2021

Wind Farm Area Shape Optimization Using Newly Developed Multi-Objective Evolutionary Algorithms

Fernando Porté Agel, Nicolas Otto Kirchner Bossi

In recent years, wind farm layout optimization (WFLO) has been extendedly developed to address the minimization of turbine wake effects in a wind farm. Considering that increasing the degrees of freedom in the decision space can lead to more efficient solu ...

MDPI2021

Convergence of adaptive algorithms for constrained weakly convex optimization

Volkan Cevher, Ahmet Alacaoglu, Yurii Malitskyi

We analyze the adaptive first order algorithm AMSGrad, for solving a constrained stochastic optimization problem with a weakly convex objective. We prove the

\tilde O(t^{-1/2})

rate of convergence for the squared norm of the gradient of Moreau envelope, ...

2021

Data-Driven Convergence Prediction of Astrobots Swarms

Denis Gillet, Jean-Paul Richard Kneib, Matin Macktoobian, Francesco Basciani

Astrobots are robotic artifacts whose swarms are used in astrophysical studies to generate the map of the observable universe. These swarms have to be coordinated with respect to various desired observations. Such coordination\footnote{\z{A coordination sa ...

2021

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 ...

2021

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Cellulan World: Interactive Platform to Learn Swarm Behaviors

UNDERGRAD: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees

Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

Finding symmetry breaking order parameters with Euclidean neural networks

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

Multikernel Regression with Sparsity Constraint

Wind Farm Area Shape Optimization Using Newly Developed Multi-Objective Evolutionary Algorithms

Convergence of adaptive algorithms for constrained weakly convex optimization

Data-Driven Convergence Prediction of Astrobots Swarms

Pareto-like sequential sampling heuristic for global optimisation

Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

Multikernel Regression with Sparsity Constraint

UNDERGRAD: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees

Wind Farm Area Shape Optimization Using Newly Developed Multi-Objective Evolutionary Algorithms

Cellulan World: Interactive Platform to Learn Swarm Behaviors

Convergence of adaptive algorithms for constrained weakly convex optimization

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

Data-Driven Convergence Prediction of Astrobots Swarms

Finding symmetry breaking order parameters with Euclidean neural networks

Pareto-like sequential sampling heuristic for global optimisation