Tabu Search-Based Metaheuristic Algorithm for Large-scale Set Covering Problems

This paper presents an algorithm for the Set Covering Problem whose centerpiece is a new primal-to-dual scheme aimed at linking any primal solution to the dual feasible vector that best reflects the quality of the primal solution. This new mechanism is used to intertwine a tabu search based primal intensive scheme with a Lagrangian based dual intensive scheme to design a dynamic primal-dual algorithm that progressively reduces the gap between upper and lower bound. The algorithm has been tested on benchmark problems from the literature: the gap between upper and lower bound in 6 instances of problems whose optimal solution is not known has been further reduced, 4 of them via improvements in the lower bound, and 4 by producing a solution that is better than the best solution provided by other procedures.

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