How to Choose Solutions for Local Search in Multiobjective Combinatorial Memetic Algorithms.
Hisao IshibuchiYasuhiro HitotsuyanagiYoshihiko WakamatsuYusuke NojimaPublished in: PPSN (1) (2010)
Keyphrases
- memetic algorithm
- multi objective
- tabu search
- genetic algorithm
- ant colony optimisation
- conflicting objectives
- multiple objectives
- evolutionary algorithm
- evolutionary computation
- crossover operator
- job shop scheduling problem
- multiobjective genetic algorithm
- uniform design
- bi objective
- pareto optimal
- combinatorial optimization
- pareto optimal solutions
- optimization algorithm
- multi objective evolutionary algorithms
- nsga ii
- multiobjective optimization
- multi objective optimization
- simulated annealing
- vehicle routing problem
- genetic operators
- assembly line balancing
- feasible solution
- optimal solution
- particle swarm optimization
- heuristic methods
- artificial bee colony
- machine learning
- artificial intelligence
- search procedures
- solution quality
- search algorithm
- optimization problems