title: A novel hybrid self-adaptive bat algorithm.
abstract: Nature-inspired algorithms attract many researchers worldwide for solving the hardest optimization problems. One of the newest members of this extensive family is the bat algorithm. To date, many variants of this algorithm have emerged for solving continuous as well as combinatorial problems. One of the more promising variants, a self-adaptive bat algorithm, has recently been proposed that enables a self-adaptation of its control parameters. In this paper, we have hybridized this algorithm using different DE strategies and applied these as a local search heuristics for improving the current best solution directing the swarm of a solution towards the better regions within a search space. The results of exhaustive experiments were promising and have encouraged us to invest more efforts into developing in this direction.
authors.affiliation: Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova 17, 2000 Maribor, Slovenia.
authors.forename: Iztok
authors.initials: I
authors.lastname: Fister
authors.affiliation: Department of Computer and Information Science, University of Macau, Avenue Padre Tomas Pereira, Taipa, Macau.
authors.forename: Simon
authors.identifier: 0000-0002-1848-7246
authors.initials: S
authors.lastname: Fong
authors.affiliation: Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova 17, 2000 Maribor, Slovenia.
authors.forename: Janez
authors.initials: J
authors.lastname: Brest
authors.affiliation: Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova 17, 2000 Maribor, Slovenia.
authors.forename: Iztok
authors.identifier: 0000-0002-9964-6957
authors.initials: I
authors.lastname: Fister
mesh_terms: D000465:Algorithms; D005246:Feedback