Blending Dynamic Programming with Monte Carlo Simulation for Bounding the Running Time of Evolutionary Algorithms.
Kirill AntonovMaxim BuzdalovArina BuzdalovaCarola DoerrPublished in: CEC (2021)
Keyphrases
- monte carlo simulation
- evolutionary algorithm
- dynamic programming
- monte carlo
- multi objective
- markov chain
- evolutionary computation
- optimization problems
- fitness function
- simulated annealing
- differential evolution algorithm
- state space
- upper bound
- multi objective optimization
- differential evolution
- genetic programming
- genetic algorithm
- additive model
- stereo matching
- evolvable hardware
- optimization algorithm
- optimal policy
- linear programming
- machine learning
- greedy algorithm
- single machine
- neural network
- evolutionary process
- reinforcement learning