Combination of meta-heuristic 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 metaheuristics 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.
|Persistent URL||dx.doi.org/10.1287/ijoc.1090.0376, hdl.handle.net/1765/118017|
|Journal||I N F O R M S Journal on Computing: charting new directions in OR and CS|
Muter, I., Birbil, S.I., & Sahin, G. (2010). Combination of meta-heuristic and exact algorithms for solving set covering-type optimization problems. I N F O R M S Journal on Computing: charting new directions in OR and CS, 22(4), 603–619. doi:10.1287/ijoc.1090.0376