CGCompiler: Automated Coarse-Grained Molecule Parametrization via Noise-Resistant Mixed-Variable Optimization
KS Stroh, PCT Souza, L Monticelli… - Journal of Chemical …, 2023 - ACS Publications
Coarse-grained force fields (CG FFs) such as the Martini model entail a predefined, fixed set
of Lennard-Jones parameters (building blocks) to model virtually all possible nonbonded …
of Lennard-Jones parameters (building blocks) to model virtually all possible nonbonded …
Optimal computing budget allocation for particle swarm optimization in stochastic optimization
Particle swarm optimization (PSO) is a popular metaheuristic for deterministic optimization.
Originated in the interpretations of the movement of individuals in a bird flock or fish school …
Originated in the interpretations of the movement of individuals in a bird flock or fish school …
Searching for structural bias in particle swarm optimization and differential evolution algorithms
AP Piotrowski, JJ Napiorkowski - Swarm Intelligence, 2016 - Springer
During the last two decades, a large number of metaheuristics have been proposed, leading
to various studies that call for a deeper insight into the behaviour, efficiency and …
to various studies that call for a deeper insight into the behaviour, efficiency and …
Data transfer via UAV swarm behaviours: Rule generation, evolution and learning
This paper presents an adaptive robotic swarm of Unmanned Aerial Vehicles (UAVs)
enabling communications between separated non-swarm devices. The swarm nodes utilise …
enabling communications between separated non-swarm devices. The swarm nodes utilise …
Adaptive data transfer methods via policy evolution for UAV swarms
This paper presents an adaptive robotic swarm of Unmanned Aerial Vehicles (UAVs)
enabling communications between separated non-swarm devices. The swarm nodes utilise …
enabling communications between separated non-swarm devices. The swarm nodes utilise …
Population statistics for particle swarm optimization: Hybrid methods in noisy optimization problems
J Rada-Vilela, M Johnston, M Zhang - Swarm and Evolutionary …, 2015 - Elsevier
Particle swarm optimization (PSO) is a metaheuristic designed to find good solutions to
optimization problems. However, when optimization problems are subject to noise, the …
optimization problems. However, when optimization problems are subject to noise, the …
A newton waveform relaxation algorithm for circuit simulation
DJ Erdman, DJ Rose - 1989 IEEE International Conference on …, 1989 - computer.org
This paper presents an adaptive robotic swarm of Unmanned Aerial Vehicles (UAVs)
enabling communications between separated non-swarm devices. The swarm nodes utilise …
enabling communications between separated non-swarm devices. The swarm nodes utilise …
[PDF][PDF] Genetic Programming Based on Novelty Search
EN Garcıa - academia.edu
Novelty Search (NS) is a unique approach towards search and optimization, where an
explicit objective function is replaced by a measure of solution novelty. However, NS has …
explicit objective function is replaced by a measure of solution novelty. However, NS has …
[PDF][PDF] Anti-swarming from the swarm robotics perspective
JC Barca - Faculty of Information Technology, Monash …, 2016 - infotech.monash.edu
This study represents the first known attempt to formulate a template for a complete anti-
swarming strategy that can be employed against adversary robotic swarms. This research is …
swarming strategy that can be employed against adversary robotic swarms. This research is …