Performance assessment of an artificial immune system multiobjective optimizer by two improved metrics

In this study, we introduce two improved assessment metrics of multiobjective optimizers, Nondominated Ratio and Spacing Distribution, and analyze their rationality and validity. Based on the concept of Immunodominance and Antibody Clonal Selection Theory, a novel multiobjective optimization algorithm, Immune Dominance Clonal Multiobjective Algorithm (IDCMA), is put forward. The simulation comparisons between IDCMA and the Strength Pareto Evolutionary Algorithm show that IDCMA has the best performance in popular metrics such as Spacing, Coverage of Two Sets and the two new metrics presented in this paper when lowdimensional multiobjective problems are concerned. The statistical results of the four metrics also show that Spacing Distribution conquers some limitations of Spacing triumphantly, and Nondominated Ratio conquers the limitation of Coverage of Two Sets that only compared between two sets. Categories and Subject Descriptors F.2.1 [Analysis of Algorithms and Problem Complexity]:...

• Type: Conference
• Year: 2005
• Where: GECCO
• Authors: Maoguo Gong, Licheng Jiao, Haifeng Du, Ronghua Shang, Bin Lu
• Keywords: Clonal Multiobjective Algorithm, GECCO 2005, Improved Assessment Metrics, Multiobjective Optimization Algorithm