Integer programming through genetic algorithms with double strings based on reference solution updating

In this paper, we extend genetic algorithms with double strings based on reference solution updating proposed by Sakawa et al. (1997, 1999) for 0-1 programming problems into integer programming problems. In addition, considering the property that an optimal solution to an integer programming problem is close to an optimal solution to the corresponding linear programming relaxation problem, we attempt to improve the search efficiency by incorporating the information about the optimal solution to the linear programming relaxation problem into genetic algorithms with double strings. Furthermore, we show the feasibility and effectiveness of the proposed method by comparison with the branch and bound method for several numerical examples.