Genetic Algorithm
OptimizePrice: $0.10/callLatency: <10msComplexity: O(g * n * d)
Quick scenarios
Evolutionary optimization that evolves a population of solutions. Tournament selection, crossover, and mutation to find optimal parameter configurations.
Click "Run Algorithm" to see results
cURL
curl -X POST https://oraclaw-api.onrender.com/api/v1/optimize/evolve \
-H "Content-Type: application/json" \
-d '{"geneLength":5,"populationSize":50,"maxGenerations":100,"bounds":{"min":0,"max":10,"type":"real"},"mutationRate":0.01,"crossoverRate":0.8,"selectionMethod":"tournament","fitnessWeights":[2,1,3,1,2]}'Input Schema
geneLength: number
populationSize: number (max 500)
maxGenerations: number (max 500)
bounds: {min, max, type}
fitnessWeights: number[]
Output Fields
bestChromosomeparetoFrontierconvergenceGenerationfitnessHistory