Notice of RetractionA Hybrid Approach Based on Immune Genetic Algorithm and Integer Linear Programming for the Container Loading Problem

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

This paper presents a novel hybrid approach for solving the Container Loading (CL) problem based on the combination of Immune Genetic Algorithm (IGA) and Integer Linear Programming (ILP) model. More precisely, an IGA engine works as a generator of reduced instances for the original CL problem, which are formulated as ILP models. These instances, in turn, are solved by ILP, and the performance measures accomplished by the respective models are interpreted as affinity values by the immune genetic algorithm, thus guiding its evolutionary process. The proposed approach was compared with five well-known algorithms taken from the literature on the public benchmarks and the extensive computational results show that the quality of the solutions is equal to or better than that obtained by the best existing algorithms.