“Incremental” Evaluation for Genetic Crossover

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Abstract

Incremental evaluation is a big advantage for trajectory-based optimization algorithms. Previously, the application of similar ideas to crossover-based algorithms, such as genetic algorithms did not seem appealing as the expected benefit would be marginal. We propose the use of an immutable data structure that stores partial evaluation results inside of the solution representation, and composing new solution from parts of previously evaluated candidates, which can speed up re-evaluation. The application of this idea to the knapsack problem shows promising results hinting at logarithmic complexity in case all genetic operators can be adapted accordingly.

OriginalspracheEnglisch
TitelComputer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers
Redakteure/-innenRoberto Moreno-Díaz, Alexis Quesada-Arencibia, Franz Pichler
Herausgeber (Verlag)Springer
Seiten396-404
Seitenumfang9
ISBN (Print)9783030450922
DOIs
PublikationsstatusVeröffentlicht - 2020
Veranstaltung17th International Conference on Computer Aided Systems Theory, EUROCAST 2019 - Las Palmas de Gran Canaria, Spanien
Dauer: 17 Feb. 201922 Feb. 2019

Publikationsreihe

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band12013 LNCS
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349

Konferenz

Konferenz17th International Conference on Computer Aided Systems Theory, EUROCAST 2019
Land/GebietSpanien
OrtLas Palmas de Gran Canaria
Zeitraum17.02.201922.02.2019

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