TY - GEN
T1 - Framework for biologically inspired graph optimization
AU - Rodionov, Alexey S.
AU - Choo, Hyunseung
AU - Nechunaeva, Kseniya A.
N1 - Publisher Copyright:
© 2011 Association for Computing Machinery. All rights reserved.
PY - 2011/2/21
Y1 - 2011/2/21
N2 - In this paper we present a framework for graph optimization called BIGOS (Biologically Inspired Graph Optimization System). It is shown how to use biological technics such as evolutional algorithms and algorithms of artificial immune system for solving different optimization problems relating to structural, resource and other restrictions. Some recommendations are given for chromosome and anti-body coding and realization of crossover and mutation operators in the case of network structure optimization.
AB - In this paper we present a framework for graph optimization called BIGOS (Biologically Inspired Graph Optimization System). It is shown how to use biological technics such as evolutional algorithms and algorithms of artificial immune system for solving different optimization problems relating to structural, resource and other restrictions. Some recommendations are given for chromosome and anti-body coding and realization of crossover and mutation operators in the case of network structure optimization.
KW - Artificial immune system
KW - Clonal selection algorithm
KW - Genetic algorithm
KW - Graph optimization
UR - https://www.scopus.com/pages/publications/79956059537
U2 - 10.1145/1968613.1968626
DO - 10.1145/1968613.1968626
M3 - Conference contribution
AN - SCOPUS:79956059537
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011
PB - Association for Computing Machinery
T2 - 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011
Y2 - 21 February 2011 through 23 February 2011
ER -