Hybridizing an evolutionary algorithm with mathematical programming techniques for multi-objective optimization.
Saúl Zapotecas MartínezCarlos A. Coello CoelloPublished in: GECCO (2008)
Keyphrases
- mathematical programming
- multi objective optimization
- evolutionary algorithm
- multi objective
- optimization problems
- linear programming
- combinatorial optimization
- evolutionary computation
- differential evolution
- hybrid evolutionary algorithm
- simulated annealing
- nsga ii
- multi objective optimization problems
- fitness function
- genetic programming
- queueing theory
- goal programming
- genetic algorithm
- pareto optimal
- genetic operators
- multi objective genetic algorithms
- multi objective genetic algorithm
- multiple objectives
- bi objective
- evolutionary strategy
- constrained optimization problems
- mixed integer linear
- vehicle routing problem
- metaheuristic
- multi objective problems
- optimization approaches
- pareto optimal solutions
- pareto frontier
- pareto optimal set
- stationary points
- particle swarm
- mutation operator
- particle swarm optimization
- controlled tabular adjustment
- solving multi objective optimization problems
- crossover operator
- optimization algorithm
- optimization method
- benchmark problems
- initial population
- multiobjective optimization