A Hybrid Evolutionary Algorithm for the Diversified Top-k Weight Clique Search Problem (Student Abstract)

Abstract The diversified top-k weight clique (DTKWC) search problem is an important generalization of the diversified top-k clique search problem, which extends the DTKC search problem by taking into account the weight of vertices. This problem involves finding at most k maximal weighted cliques that cover maximum weight of vertices with low overlapping in a given graph. In this study, a mixed integer linear program constraint formulation is proposed to model DTKWC search problem and an efficient hybrid evolutionary algorithm (HEA-D) based on some heuristic strategies is proposed to tackle it. Experiments on two sets of 110 graphs show that HEA-D outperforms the state-of-art methods.