A stochastic approach for the one-dimensional bin-packing problems

The authors present a novel stochastic approach called the annealing-genetic algorithm for the one-dimensional bin-packing problem. This approach incorporates genetic algorithms into simulated annealing (SA) to improve the performance of SA. The genetic approach to SA seems to facilitate the exhaustive and parallel treatment of the problem and to increase the probability of finding global minima. The empirical results show that the quality of the solution obtained with this approach is better than or equal to that of the FFD (first-fit-decreasing) in the average cases but is better than that of the FFD in all the known worst cases. Unlike the FFD, no nonmonotone anomaly has been found in the proposed approach