Title :
Improved comparative partner selection with brood recombination for genetic programming
Author :
Aslam, Muhammad Waqar ; Zhechen Zhu ; Nandi, A.K.
Author_Institution :
Univ. of Liverpool, Liverpool, UK
Abstract :
The aim of all evolutionary methods is to find the best solution from search space without testing every solution in search space. This study employs strengths and weaknesses of solutions for finding the best solution of any problem in genetic programming. The strengths and weaknesses are used to assist in finding the right partners (solutions) during crossover operation. The probability of crossover between two solutions is evaluated using relative strengths and weaknesses as well as overall strengths of solutions (Improved Comparative Partner Selection (ICPS)). The solutions qualifying for crossover through ICPS criteria are supposed to produce better solutions and are allowed to produce more children through brood recombination. The brood recombination helps to exploit the search space close to the optimum solution more efficiently. The proposed method is applied on different benchmarking problems and results demonstrate that the method is highly efficient in exploring the search space.
Keywords :
genetic algorithms; probability; search problems; ICPS criteria; benchmarking problems; brood recombination; crossover probability; evolutionary methods; genetic programming; improved comparative partner selection; optimum solution; search space; Educational institutions; Genetic programming; Iterative closest point algorithm; Multiplexing; Sociology; Statistics; Training; Brood recombination; Diversity in genetic programming; Improved comparative partner selection;
Conference_Titel :
Machine Learning for Signal Processing (MLSP), 2013 IEEE International Workshop on
Conference_Location :
Southampton
DOI :
10.1109/MLSP.2013.6661901