English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Particle accelerators are invaluable tools for research in the basic andapplied sciences, in fields such as materials science, chemistry, thebiosciences, particle physics, nuclear physics and medicine. The design,commissioning, and operation of accelerator facilities is a non-trivial task,due to the large number of control parameters and the complex interplay ofseveral conflicting design goals. We propose to tackle this problem by means ofmulti-objective optimization algorithms which also facilitate a paralleldeployment. In order to compute solutions in a meaningful time frame a fast andscalable software framework is required. In this paper, we present theimplementation of such a general-purpose framework for simulation-basedmulti-objective optimization methods that allows the automatic investigation ofoptimal sets of machine parameters. The implementation is based on amaster/slave paradigm, employing several masters that govern a set of slavesexecuting simulations and performing optimization tasks. Using evolutionaryalgorithms as the optimizer and OPAL as the forward solver, validationexperiments and results of multi-objective optimization problems in the domainof beam dynamics are presented. The high charge beam line at the ArgonneWakefield Accelerator Facility was used as the beam dynamics model. The 3D beamsize, transverse momentum, and energy spread were optimized.

A Parallel General Purpose Multi-Objective Optimization Framework, with Application to Beam Dynamics