title: Seven-spot ladybird optimization: a novel and efficient metaheuristic algorithm for numerical optimization.
abstract: This paper presents a novel biologically inspired metaheuristic algorithm called seven-spot ladybird optimization (SLO). The SLO is inspired by recent discoveries on the foraging behavior of a seven-spot ladybird. In this paper, the performance of the SLO is compared with that of the genetic algorithm, particle swarm optimization, and artificial bee colony algorithms by using five numerical benchmark functions with multimodality. The results show that SLO has the ability to find the best solution with a comparatively small population size and is suitable for solving optimization problems with lower dimensions.
authors.affiliation: School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.
authors.forename: Peng
authors.initials: P
authors.lastname: Wang
authors.affiliation: School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.
authors.forename: Zhouquan
authors.initials: Z
authors.lastname: Zhu
authors.affiliation: School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.
authors.forename: Shuai
authors.initials: S
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D000818:Animals; D001517:Coleoptera / Q000502:physiology*; D003198:Computer Simulation; D003661:Decision Support Techniques; D005247:Feeding Behavior / Q000502:physiology*; D008954:Models, Biological; D009716:Numerical Analysis, Computer-Assisted; D011235:Predatory Behavior / Q000502:physiology*