Testing of a spreading mechanism to promote diversity in multi-objective particle swarm optimization
β Scribed by Knight, Joshua T.; Singer, David J.; Collette, Matthew D.
- Book ID
- 125367096
- Publisher
- Springer US
- Year
- 2014
- Tongue
- English
- Weight
- 1019 KB
- Volume
- 16
- Category
- Article
- ISSN
- 1389-4420
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π SIMILAR VOLUMES
## a b s t r a c t In multi-objective particle swarm optimization (MOPSO) algorithms, finding the global optimal particle (gBest) for each particle of the swarm from a set of non-dominated solutions is very difficult yet an important problem for attaining convergence and diversity of solutions. Fir
From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more.Β It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective inte