Precision in High Dimensional Optimisation of Global Tasks with Unknown Solutions

Research output: Chapter in Book/Report/Published conference proceedingChapter

Abstract

High dimensional optimisation is a challenge for most of the available search methods. Resolving global and constrained task seems to be even harder and exploration of tasks with unknown solutions can be seen very rare in the literature and requires more research efforts. This article analyses optimisation of high dimensional global, including constrained, tasks with unknown solutions. Reviewed and analysed are experimental results precision, possibilities for trapping in local sub-optima and adaptation to unknown search spaces.
Original languageEnglish
Title of host publicationLarge-Scale Scientific Computing
Subtitle of host publicationLSSC 2019. Lecture Notes in Computer Science
EditorsIvan Lirkov, Svetozar Margenov
Place of PublicationCham
PublisherSpringer Nature
Pages524-529
Number of pages6
Volume11958
ISBN (Electronic)978-3-030-41032-2
ISBN (Print)978-3-030-41031-5
DOIs
Publication statusPublished - 13 Jan 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11958 LNCS

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