On the fitness of high order schema of a linear-weighted coded genetic algorithm

Hongqiang Mo, Zhong Li, Jin Bae Park, Young Hoon Joo, Xiangyang Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

According to Schema Theorem, the larger the fitness value of a schema is, the higher the chance of the sub-space corresponding to the schema being chosen for searching is. Therefore, the coding of a genetic algorithm should be designed to produces short building blocks at as more fixed positions of the strings as possible. In this paper, an upper and lower bounds of the fitness values of order-n building blocks are given in terms of the maximal fitness values of order-1 building blocks. It is shown that, if a linear-weighted coding supplies order-1 building blocks at most of the loci of the strings, then there is sure to be remarkable fitness differences among high order schemata. In such case, the trajectory of the fitness function contains peaks, and diversity loss is likely to occur in the local search within these peaks.

Original languageEnglish
Title of host publicationWorld Scientific Proceedings Series on Computer Engineering and Information Science 1; Computational Intelligence in Decision and Control - Proceedings of the 8th International FLINS Conference
PublisherWorld Scientific Publishing Co. Pte Ltd
Pages713-718
Number of pages6
ISBN (Print)981279946X, 9789812799463
DOIs
Publication statusPublished - 2008
EventComputational Intelligence in Decision and Control - 8th International FLINS Conference - Madrid, Spain
Duration: 2008 Sept 212008 Sept 24

Publication series

NameWorld Scientific Proceedings Series on Computer Engineering and Information Science 1; Computational Intelligence in Decision and Control - Proceedings of the 8th International FLINS Conference

Other

OtherComputational Intelligence in Decision and Control - 8th International FLINS Conference
Country/TerritorySpain
CityMadrid
Period08/9/2108/9/24

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Information Systems and Management
  • Control and Systems Engineering

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