Title :
Running Up Those Hills: Multi-modal search with the niching migratory multi-swarm optimiser
Author :
Fieldsend, Jonathan E.
Author_Institution :
Coll. of Eng., Math. & Phys. Sci., Univ. of Exeter, Exeter, UK
Abstract :
We present a new multi-modal evolutionary opti-miser, the niching migratory multi-swarm optimiser (NMMSO), which dynamically manages many particle swarms. These sub-swarms are concerned with optimising separate local modes, and employ measures to allow swarm elements to migrate away from their parent swarm if they are identified as being in the vicinity of a separate peak, and to merge swarms together if they are identified as being concerned with the same peak. We employ coarse peak identification to facilitate the mode identification required. Swarm members are not constrained to particular sub-regions of the parameter space, however members are initialised in the vicinity of a swarm´s local mode estimate. NMMSO is shown to cope with a range of problem types, and to produce results competitive with the state-of-the-art on the CEC 2013 multi-modal optimisation competition test problems, providing new benchmark results in the field.
Keywords :
evolutionary computation; particle swarm optimisation; search problems; CEC 2013 multimodal optimisation competition test problems; NMMSO; coarse peak identification; mode identification; multimodal evolutionary optimiser; multimodal search; niching migratory multiswarm optimiser; parameter space; particle swarms; separate local mode optimization; sub-swarms; swarm elements; swarm local mode estimate; Algorithm design and analysis; Heuristic algorithms; Merging; Optimization; Particle swarm optimization; Sociology; Statistics;
Conference_Titel :
Evolutionary Computation (CEC), 2014 IEEE Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6626-4
DOI :
10.1109/CEC.2014.6900309