TY - GEN
T1 - Assessing the performance of two immune inspired algorithms and a hybrid genetic algorithm for function optimisation
AU - Timmis, Jon
AU - Edmonds, Camilla
AU - Kelsey, Johnny
PY - 2004
Y1 - 2004
N2 - Do Artificial Immune Systems (AIS) have something to offer the world of optimisation? Indeed do they have any new to offer at all? This paper reports the initial findings of a comparison between two immune inspired algorithms and a hybrid genetic algorithm for function optimisation. This work is part of ongoing research which forms part of a larger project to assess the performance and viability of AIS. The investigation employs standard benchmark functions, and demonstrates that for these functions the opt-aiNET algorithm, when compared to the B-cell algorithm and hybrid GA, on average, takes longer to find the solution, without necessarily a better quality solution. Reasons for these differences are proposed and it is acknowledge that this is preliminary empirical work. It is felt that a more theoretical approach may well be required to ascertain real performance and applicability issues.
AB - Do Artificial Immune Systems (AIS) have something to offer the world of optimisation? Indeed do they have any new to offer at all? This paper reports the initial findings of a comparison between two immune inspired algorithms and a hybrid genetic algorithm for function optimisation. This work is part of ongoing research which forms part of a larger project to assess the performance and viability of AIS. The investigation employs standard benchmark functions, and demonstrates that for these functions the opt-aiNET algorithm, when compared to the B-cell algorithm and hybrid GA, on average, takes longer to find the solution, without necessarily a better quality solution. Reasons for these differences are proposed and it is acknowledge that this is preliminary empirical work. It is felt that a more theoretical approach may well be required to ascertain real performance and applicability issues.
UR - http://www.scopus.com/inward/record.url?scp=4344595528&partnerID=8YFLogxK
M3 - Conference Proceeding (Non-Journal item)
AN - SCOPUS:4344595528
SN - 0780385152
SN - 9780780385153
T3 - Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004
SP - 1044
EP - 1051
BT - Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004
T2 - Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Y2 - 19 June 2004 through 23 June 2004
ER -