Combination of meta-heuristics and exact algorithms for solving set-covering type optimization problems

We propose a new generic framework for solving combinatorial optimization problems that can be modeled as a set-covering problem. The proposed algorithmic framework combines meta-heuristics with exact algorithms through a guiding mechanism based on diversification and intensification decisions. After presenting this generic framework, we extensively demonstrate its application to the vehicle routing problem with time windows. We then conduct a thorough computational study on a set of well-known test problems, where we show that the proposed approach not only finds solutions that are very close to the best-known solutions reported in the literature but also improves them. We finally set up an experimental design to analyze the effects of different parameters used in the proposed algorithm.