Genetic algorithms with double strings for 0–1 programming problems

In this paper, genetic algorithms with double strings for 0–1 knapsack problems are first revisited together with some modifications and computational experiments. Then the genetic algorithms with double strings for 0–1 knapsack problems are extended to deal with more general 0–1 programming problems involving both positive and negative coefficients in the constraints. Especially, new decoding algorithms for double strings using reference solutions both without and with the reference solution updating procedure are proposed so that each of individuals is decoded to the corresponding feasible solution for the general 0–1 programming problems. The efficiency and effectiveness of the proposed methods are investigated by comparing them with a branch and bound method with respect to the accuracy of an approximate solution and the processing time through a number of numerical experiments.