An Integer Programming-based Local Search for Large-scale Maximal Covering Problems

Maximal covering problem (MCP) is classified as a linear integer optimization problem which can be effectively solved by integer programming technique. However, as the problem size grows, integerprogramming requires excessive time to get an optimal solution. This paper suggests a method for applying integer programming-based local search (IPbLS) to solve large-scale maximal covering problems. IPbLS, which is a hybrid technique combining integer programming and local search, is a kind of local search using integer programming for neighbor generation. IPbLS itself is very effective for MCP. In addition, we improve the performance of IPbLS for MCP through problem reduction based on the current solution. Experimental results show that the proposed method considerably outperforms any other local search techniques and integer programming.