Improvements to penalty-based evolutionary algorithms for the multi-dimensional knapsack problem using a gene-based adaptive mutation approach.
Sima UyarGülsen EryigitPublished in: GECCO (2005)
Keyphrases
- knapsack problem
- evolutionary algorithm
- multi dimensional
- optimization problems
- adaptive mutation
- premature convergence
- genetic algorithm
- mutation operator
- differential evolution
- multi objective
- test problems
- evolutionary computation
- metaheuristic
- dynamic programming
- fitness function
- optimal solution
- particle swarm
- differential evolution algorithm
- genetic programming
- exact algorithms
- optimization method
- nsga ii
- penalty function
- objective function
- np hard
- crossover operator
- control parameters
- multi objective optimization
- benchmark problems
- simulated annealing
- optimization methods
- evolution strategy
- traveling salesman problem
- convergence speed
- neural network
- tabu search
- optimization algorithm
- genetic operators
- high dimensional
- evolutionary process
- greedy algorithm
- computational complexity
- combinatorial optimization
- computational intelligence
- initial population
- evolutionary strategy