A theoretical assessment of solution quality in evolutionary algorithms for the knapsack problem.
Jun HeBoris MitavskiyYuren ZhouPublished in: IEEE Congress on Evolutionary Computation (2014)
Keyphrases
- knapsack problem
- solution quality
- evolutionary algorithm
- optimization problems
- simulated annealing
- optimal solution
- test problems
- population diversity
- combinatorial optimization problems
- computational effort
- multi objective
- evolutionary computation
- nsga ii
- metaheuristic
- feasible solution
- fitness function
- test instances
- computational efficiency
- multi objective optimization
- benchmark problems
- exact algorithms
- differential evolution
- genetic programming
- tabu search
- np hard
- genetic algorithm ga
- branch and bound
- multidimensional knapsack problem
- evolutionary strategy
- tabu search algorithm
- linear programming
- dynamic programming
- maximum profit
- mutation operator
- objective function
- randomly generated test instances
- combinatorial optimization
- optimization algorithm
- lower bound
- particle swarm optimization pso
- traveling salesman problem
- resource consumption
- ant colony optimization
- implicit enumeration
- genetic algorithm