An Adaptive Hybrid Immune Genetic Algorithm for Maximum Cut Problem.

The goal of maximum cut problem is to partition the vertex set of an undirected graph into two parts in order to maximize the cardinality of the set of edges cut by the partition. This paper proposes an Adaptive Hybrid Immune Genetic Algorithm, which includes key techniques such as vaccine abstraction, vaccination and affinity-based selection. A large number of instances have been simulated, and the results show that proposed algorithm is superior to existing algorithms. [ABSTRACT FROM AUTHOR]