Multi-objective optimization with diversity preserving mixture-based iterated density estimation evolutionary algorithms

Multi-objective optimization with diversity preserving mixture-based iterated density estimation evolutionary algorithms

Stochastic optimization by learning and using probabilistic models has received an increasing amount of attention over the last few years. Algorithms within this field estimate the probability distribution of a selection of the available solutions and subsequently draw more samples from the estimated probability distribution. The resulting algorithms have displayed a good performance on a wide ...

Multi-Obje tive Mixture-based Iterated Density Estimation Evolutionary Algorithms

Privacy-Preserving Multi-Objective Evolutionary Algorithms

Existing privacy-preserving evolutionary algorithms are limited to specific problems securing only cost function evaluation. This lack of functionality and security prevents their use for many security sensitive business optimization problems, such as our use case in collaborative supply chain management. We present a technique to construct privacypreserving algorithms that address multi-object...

The ensemble clustering with maximize diversity using evolutionary optimization algorithms

Data clustering is one of the main steps in data mining, which is responsible for exploring hidden patterns in non-tagged data. Due to the complexity of the problem and the weakness of the basic clustering methods, most studies today are guided by clustering ensemble methods. Diversity in primary results is one of the most important factors that can affect the quality of the final results. Also...

Hybrid Evolutionary Multi-Objective Optimization Algorithms

This paper examines how the search ability of evolutionary multi-objective optimization (EMO) algorithms can be improved by the hybridization with local search through computational experiments on multi-objective permutation flowshop scheduling problems. The task of EMO algorithms is to find a variety of nondominated solutions of multi-objective optimization problems. First we describe our mult...