Improvement heuristic for solving the one-dimensional bin-packing problem

We develop in the present paper a genetic algorithm for the one-dimensional bin packing problem. This algorithm performs a series of perturbations in an attempt to improve the current solution, applying some problem dependant genetic operators. Our procedure is efficient and easy to implement. We apply it to several benchmark instances taken from some problem sets and compare our results to those found in the literature. We find that our algorithm is able to generates competitive results compared to the best methods known so far and computes, for the first time, one optimal solution for one open benchmark instance.