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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 106
PROCEEDINGS OF THE TWELFTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY
Edited by:
Paper 170

Panobbgo: Parallel Noisy Black-Box Global Optimization

H. Schilly

Institute of Mathematics, University of Vienna, Austria

Full Bibliographic Reference for this paper
H. Schilly, "Panobbgo: Parallel Noisy Black-Box Global Optimization", in , (Editors), "Proceedings of the Twelfth International Conference on Computational Structures Technology", Civil-Comp Press, Stirlingshire, UK, Paper 170, 2014. doi:10.4203/ccp.106.170
Keywords: black-box optimization, derivative-free optimization, parallelization, distributed, heuristic, experimentation..

Summary
Most existing black-box optimization tools evaluate the objective function sequentially. The experimental optimization framework Panobbgo aims to support parallel evaluation of the objective function inherently in its core. Additionally, a modularized component architecture with a centralized, event-based orchestration mechanism, encourages incremental improvements and experiments with new algorithmic ideas.

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