DocumentCode
2466097
Title
Evolving Efficient Recursive Sorting Algorithms
Author
Agapitos, Alexandros ; Lucas, Simon M.
Author_Institution
Essex Univ., Colchester
fYear
0
fDate
0-0 0
Firstpage
2677
Lastpage
2684
Abstract
Object Oriented Genetic Programming (OOGP) is applied to the task of evolving general recursive sorting algorithms. We studied the effects of language primitives and fitness functions on the success of the evolutionary process. For language primitives, these were the methods of a simple list processing package. Five different fitness functions based on sequence disorder were evaluated. The time complexity of the successfully evolved algorithms was measured experimentally in terms of the number of method invocations made, and for the best evolved individuals this was best approximated as O(n times log(n)). This is the first time that sorting algorithms of this complexity have been evolved.
Keywords
computational complexity; evolutionary computation; genetic algorithms; object-oriented languages; object-oriented programming; OOGP; evolutionary process; fitness function; language primitives; object oriented genetic programming; recursive sorting algorithms; time complexity; Computer industry; Computer science; Control systems; Genetic programming; Iterative algorithms; Java; Object oriented programming; Packaging; Sorting; Time measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-9487-9
Type
conf
DOI
10.1109/CEC.2006.1688643
Filename
1688643
Link To Document