A hybrid algorithm based on MOEA/D and local search for multiobjective optimization.
Man-Fai LeungSin Chun NgPublished in: CEC (2020)
Keyphrases
- hybrid algorithm
- multiobjective optimization
- multi objective
- nsga ii
- genetic algorithm
- particle swarm optimization
- tabu search
- multiobjective evolutionary algorithm
- optimal solution
- simulated annealing
- global search
- evolutionary algorithm
- test problems
- differential evolution
- optimization algorithm
- multi objective optimization
- particle swarm optimization pso
- hybrid algorithms
- pareto optimal
- memetic algorithm
- hybrid optimization algorithm
- convergence speed
- pareto optimal solutions
- initial solution
- multi objective evolutionary algorithms
- metaheuristic
- objective function
- optimization method
- pareto dominance
- global optimization
- min max
- standard test problems
- feasible solution
- multiple objectives
- swarm intelligence
- artificial immune system
- imperialist competitive algorithm
- search algorithm
- particle swarm optimization algorithm
- ant colony optimization
- pso algorithm
- evolutionary computation
- solution quality
- artificial bee colony
- initial population
- combinatorial optimization
- search space
- job shop scheduling problem
- particle swarm
- np hard
- scheduling problem
- mutation operator
- fitness function
- optimization problems
- nonlinear integer programming
- bi objective
- genetic algorithm ga
- crossover operator
- motif discovery
- branch and bound
- evolution strategy
- lower bound
- benchmark problems
- machine learning