A multiobjective genetic algorithm to uncover community structure in complex network is proposed. The algorithm optimizes two objective functions able to identify densely connecte...
We present two novel perturbation-based linkage learning algorithms that extend LINC [5]; a version of LINC optimised for decomposition tasks (oLINC) and a hierarchical version of...
We present a Kernighan-Lin style local improvement heuristic for genetic algorithms. We analyze the run-time cost of the heuristic. We demonstrate through experiments that the heur...
The Building Block Hypothesis suggests that Genetic Algorithms (GAs) are well-suited for hierarchical problems, where efficient solving requires proper problem decomposition and a...
Differential evolution (DE) has emerged as one of the fast, robust, and efficient global search heuristics of current interest. This paper describes an application of DE to the aut...