Solving the Pareto front for multiobjective Markov chains using the minimum Euclidean distance gradient-based optimization method.
Julio B. ClempnerAlexander S. PoznyakPublished in: Math. Comput. Simul. (2016)
Keyphrases
- multi objective
- euclidean distance
- optimization method
- markov chain
- optimization algorithm
- evolutionary algorithm
- genetic algorithm
- multi objective optimization
- multiobjective optimization
- differential evolution
- optimization methods
- steady state
- transition probabilities
- particle swarm
- distance metric
- optimization procedure
- nsga ii
- distance measure
- similarity measure
- distance function
- particle swarm optimization
- state space
- random walk
- simulated annealing
- data points
- markov processes
- multiple objectives
- optimization problems
- feature vectors
- nonlinear optimization
- mahalanobis distance
- objective function
- pareto optimal
- probabilistic automata
- manhattan distance
- dimensionality reduction
- particle swarm optimization pso
- metaheuristic
- nelder mead simplex
- neural network
- sample size
- high dimensional