Upper and lower bounds on unrestricted black-box complexity of jumpn,ℓ

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Abstract

We analyse the unrestricted black-box complexity of Jumpn,ℓ functions. For upper bounds, we present three algorithms for small, medium and extreme values of ℓ We present a matrix lower bound theorem which is capable of giving better lower bounds than a general information theory approach if one is able to assign different types to queries and define relationships between them. Using this theorem, we prove lower bounds for Jump separately for odd and even values of n. For several cases, notably for extreme Jump, the first terms of lower and upper bounds coincide.

Original languageEnglish
Title of host publicationEvolutionary Computation in Combinatorial Optimization - 15th European Conference, EvoCOP 2015, Proceedings
EditorsGabriela Ochoa, Francisco Chicano
PublisherSpringer Verlag
Pages209-221
Number of pages13
ISBN (Electronic)9783319164670
DOIs
Publication statusPublished - 1 Jan 2015
Event15th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2015 - Copenhagen, Denmark
Duration: 8 Apr 201510 Apr 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9026
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2015
Country/TerritoryDenmark
CityCopenhagen
Period8/04/1510/04/15

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