In order to address the difficult issue of parameter setting within a diversity-based Multi-objective Evolutionary Algorithm (MOEA), we recently proposed a hybrid control scheme based on both Fuzzy Logic Controllers (FLCs) and Hyper-heuristics (HHs). The method simultaneously adapts both symbolic and numeric parameters and was shown to be effective when controlling a diversity-based MOEA applied to a range of benchmark problems. Here, we show that the hybrid control scheme generalises to other meta-heuristics by using it to adapt several parameters of a diversity-based multi-objective Memetic Algorithm (MA) applied to a Frequency Assignment Problem (FAP). Using real-world instances of the FAP, we demonstrate that our proposed parameter control method outperforms parameter tuning of the MA. The results provide new evidence that the method can be successfully applied to significantly more complex problems than the benchmarks previously tested.

UNLABELLED: We introduce IonGAP, a publicly available Web platform designed for the analysis of whole bacterial genomes using Ion Torrent sequence data. Besides assembly, it integrates a variety of comparative genomics, annotation and bacterial classification routines, based on the widely used FASTQ, BAM and SRA file formats. Benchmarking with different datasets evidenced that IonGAP is a fast, powerful and simple-to-use bioinformatics tool. By releasing this platform, we aim to translate low-cost bacterial genome analysis for microbiological prevention and control in healthcare, agroalimentary and pharmaceutical industry applications. AVAILABILITY AND IMPLEMENTATION: IonGAP is hosted by the ITER's Teide-HPC supercomputer and is freely available on the Web for non-commercial use at http://iongap.hpc.iter.es. CONTACT: [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.