Statements (59)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
Search Algorithm
Metaheuristic Optimization Algorithm |
| gptkbp:advantage |
Robustness
Parallelism Computational Cost Parameter Sensitivity Global Search Capability Premature Convergence |
| gptkbp:appliesTo |
gptkb:Bioinformatics
gptkb:Knapsack_Problem gptkb:Traveling_Salesman_Problem Image Processing Data Mining Control Systems Resource Allocation Financial Modeling Game Playing Feature Selection Circuit Design Function Optimization Neural Network Training Scheduling Problems |
| gptkbp:basedOn |
gptkb:Natural_Selection
|
| gptkbp:category |
Heuristic Algorithm
Population-based Algorithm Stochastic Algorithm |
| gptkbp:encodesSolutionAs |
gptkb:tree
String Permutation Bitstring |
| gptkbp:foundIn |
Solution Space
|
| gptkbp:hasComponent |
gptkb:Mutation
gptkb:Chromosome Selection Generation Population Crossover Fitness Function |
| https://www.w3.org/2000/01/rdf-schema#label |
Genetic Algorithm
|
| gptkbp:inspiredBy |
Biological Evolution
|
| gptkbp:introduced |
gptkb:John_Holland
|
| gptkbp:introducedIn |
1975
|
| gptkbp:operator |
Crossover Operator
Mutation Operator Selection Operator |
| gptkbp:relatedTo |
gptkb:Particle_Swarm_Optimization
gptkb:Evolutionary_Algorithm Differential Evolution Genetic Programming |
| gptkbp:usedIn |
gptkb:Machine_Learning
gptkb:artificial_intelligence gptkb:robot gptkb:Game_Theory Scheduling Engineering Design Optimization Problems |
| gptkbp:bfsParent |
gptkb:Simulated_Annealing
|
| gptkbp:bfsLayer |
6
|