An intercell scheduling approach using shuffled frog leaping algorithm and genetic programming

To deal with the intercell scheduling problem with limited transportation capabilities, a shuffled frog leaping algorithm-based hyperheuristic approach with genetic programming is developed in this paper. The proposed approach develops an improved shuffled frog leaping algorithm to search the combinations of heuristic rules for the addressed problem. Meanwhile, genetic programming is also introduced into the proposed algorithm to generate well-performing heuristic rules as an extension to the predefined candidate heuristic rules. Experimental results show that the improved shuffled frog leaping algorithm is efficient to search the outperforming combinations of the heuristic rules, and that the heuristic rules generated via genetic programming can obviously improve the quality of the candidate rule set, therefore providing better performance.