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A new optimization method: Big Bang-Big Crunch
Osman K. Erol
*
,
Ibrahim Eksin
*
Corresponding author for this work
Department of Control and Automation Engineering
Research output
:
Contribution to journal
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Article
›
peer-review
1278
Citations (Scopus)
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Keyphrases
Big Crunch
100%
Big Bang
100%
Optimization Methods
100%
Big Bang Big Crunch
100%
Genetic Algorithm
66%
Energy Dissipation
33%
Optimization Algorithm
33%
Benchmark Functions
33%
Universe Evolution
33%
Center of Mass
33%
Genetic Search
33%
Search Algorithm
33%
Search Methods
33%
Random Selection
33%
Evolutionary Algorithms
33%
Random Variation
33%
Randomly Distributed
33%
Simulated Annealing Method
33%
Population-based Search
33%
Minimal Cost
33%
Classical Genetics
33%
Cost-based Approach
33%
Engineering
Optimization Method
100%
Big Bang
100%
Genetic Algorithm
33%
Energy Dissipation
16%
Representative Point
16%
Random Variation
16%
Search Algorithm
16%
Random Selection
16%
Mathematics
Big Crunch
100%
Genetic Algorithm
33%
Superiority
16%
Evolutionary Algorithm
16%
test function φ
16%
Random Point
16%
Search Algorithm
16%
Energy Dissipation
16%
Representative Point
16%
Random Variation
16%
Physics
Genetic Algorithm
100%
Center of Mass
50%
Simulated Annealing
50%