A Restart Local Search for Solving Diversified Top-k Weight Clique Search Problem

Diversified top-k weight clique (DTKWC) search problem is an important generalization of the diversified (DTKC) with practical applications. The aims to k maximal cliques that can cover maximum in a vertex weighted graph. In this work, we propose novel local algorithm called TOPKWCLQ for DTKWC which mainly includes two strategies. First, restart strategy adopted, repeated construction and updating processes set. Second, scoring heuristic designed by giving different priorities candidate Meanwhile, constraint model constructed such research concerns be evaluated. Experimental results show proposed outperforms than comparison on large-scale real-world graphs.