A novel modified BSA inspired by species evolution rule and simulated annealing principle for constrained engineering optimization problems.
Hailong WangZhongbo HuYuqiu SunQinghua SuXuewen XiaPublished in: Neural Comput. Appl. (2019)
Keyphrases
- simulated annealing
- optimization problems
- evolutionary algorithm
- metaheuristic
- optimization methods
- combinatorial optimization
- tabu search
- horizontal gene transfer
- constrained problems
- evolutionary history
- genetic algorithm
- simulated annealing algorithm
- objective function
- artificial intelligence
- multi objective
- optimization method
- stochastic search
- genetic algorithm ga
- cost function
- natural selection
- multi objective optimization
- solution quality
- computer science
- design process
- evolutionary robotics
- global optimum
- optimization criteria
- engineering students
- software engineering
- artificial life
- hill climbing
- rule sets
- genetic programming
- optimization algorithm
- association rules
- ant colony optimization
- differential evolution
- traveling salesman problem
- particle swarm optimization pso
- search algorithm
- fitness function
- rule learning
- rule induction
- case study
- predator prey
- gene duplication
- search space
- sequenced genomes
- neural network
- reversible jump mcmc