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Ringed Seal Search for Global Optimization via a Sensitive Search Model
- Source :
- PLoS ONE, PLoS ONE, Vol 11, Iss 1, p e0144371 (2016)
- Publication Year :
- 2016
- Publisher :
- Public Library of Science, 2016.
-
Abstract
- The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS) is introduced. It is inspired by the natural behavior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emitted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and validations were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of convergence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive) and exploitation (intensive) of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be used in global optimization problems.
- Subjects :
- Seals, Earless
RSS
lcsh:Medicine
Social Sciences
02 engineering and technology
Mathematical and Statistical Techniques
0202 electrical engineering, electronic engineering, information engineering
Psychology
lcsh:Science
Cuckoo search
Physics
Mammals
Multidisciplinary
Animal Behavior
Behavior, Animal
Mathematical Models
Applied Mathematics
Simulation and Modeling
Swarm behaviour
computer.file_format
Random walk
Habitats
Smell
Physical Sciences
Vertebrates
Benchmark (computing)
020201 artificial intelligence & image processing
Sensory Perception
Imitation
Algorithm
Algorithms
Research Article
Optimization
Death Rates
Bears
Research and Analysis Methods
Population Metrics
020204 information systems
Genetic algorithm
Animals
Computer Simulation
Global optimization
Metaheuristic
Demography
Behavior
Population Biology
lcsh:R
Ecology and Environmental Sciences
Organisms
Biology and Life Sciences
Models, Theoretical
Random Walk
People and Places
lcsh:Q
computer
Zoology
Mathematics
Neuroscience
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 11
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....18d082a3753df75444559af9bd9737c7