Distributed Multi-Objective Metaheuristics for Real-World Structural Optimization Problems.
Francisco LunaGustavo R. ZavalaAntonio J. NebroJuan José DurilloCarlos A. Coello CoelloPublished in: Comput. J. (2016)
Keyphrases
- optimization problems
- multi objective
- evolutionary algorithm
- real world
- metaheuristic
- objective function
- nsga ii
- particle swarm optimization
- multi objective optimization
- optimization algorithm
- multi objective optimization problems
- evolutionary computation
- simulated annealing
- genetic algorithm
- multiple objectives
- traveling salesman problem
- data sets
- distributed systems
- knapsack problem
- multiobjective optimization
- combinatorial optimization
- multiobjective evolutionary algorithms
- benchmark problems
- genetic programming
- wide range
- multiobjective evolutionary algorithm
- optimization methods
- cost function
- scatter search
- bi objective
- multi objective evolutionary
- fitness function
- differential evolution
- synthetic data
- distributed environment
- data mining
- multi agent
- lightweight
- multi objective genetic algorithms
- optimization method
- optimum design
- cooperative
- conflicting objectives
- evolutionary optimization
- search space
- trade off
- peer to peer
- test problems
- computer networks
- pareto optimal
- np hard
- multi agent systems
- communication cost
- mobile agents
- case study
- ant colony optimization