# On the Taxonomy of Optimization Problems Under Estimation of Distribution Algorithms

@article{Echegoyen2013OnTT, title={On the Taxonomy of Optimization Problems Under Estimation of Distribution Algorithms}, author={Carlos Echegoyen and Alexander Mendiburu and Roberto Santana and Jos{\'e} Antonio Lozano}, journal={Evolutionary Computation}, year={2013}, volume={21}, pages={471-495} }

Understanding the relationship between a search algorithm and the space of problems is a fundamental issue in the optimization field. In this paper, we lay the foundations to elaborate taxonomies of problems under estimation of distribution algorithms (EDAs). By using an infinite population model and assuming that the selection operator is based on the rank of the solutions, we group optimization problems according to the behavior of the EDA. Throughout the definition of an equivalence relation…

## 19 Citations

### Comprehensive characterization of the behaviors of estimation of distribution algorithms

- Computer Science, MathematicsTheor. Comput. Sci.
- 2015

### Structural coherence of problem and algorithm: An analysis for EDAs on all 2-bit and 3-bit problems

- Computer Science2015 IEEE Congress on Evolutionary Computation (CEC)
- 2015

This work performs an exhaustive analysis of all 2 and 3 bit problems, grouped into classes based on mononotic invariance, and shows that each class has a minimal Walsh structure that can be used to solve the problem.

### Extending distance-based ranking models in estimation of distribution algorithms

- Computer Science2014 IEEE Congress on Evolutionary Computation (CEC)
- 2014

This paper extends the use of distance-based ranking models in the framework of EDAs by introducing new distance metrics such as Cayley and Ulam, and shows that Mallows-Ulam EDA is the most stable algorithm among the studied proposals.

### The role of Walsh structure and ordinal linkage in the optimisation of pseudo-Boolean functions under monotonicity invariance

- Computer Science
- 2016

Insight is developed into the relationship between function structure and problem difficulty for optimisation, which may be used to direct the development of novel algorithms.

### Pairwise independence and its impact on Estimation of Distribution Algorithms

- Computer ScienceSwarm Evol. Comput.
- 2016

### Customized Selection in Estimation of Distribution Algorithms

- Computer ScienceSEAL
- 2014

This paper proposes to use different selection probabilities to learn the structural and parametric components of the probabilistic graphical models.

### On the model updating operators in univariate estimation of distribution algorithms

- MathematicsNatural Computing
- 2015

The role of the selection operation—that stochastically discriminate between individuals based on their merit—on the updating of the probability model in univariate estimation of distribution algorithms is investigated and a family of operators that generalize current model updating mechanisms is proposed.

### Are we generating instances uniformly at random?

- Computer Science2017 IEEE Congress on Evolutionary Computation (CEC)
- 2017

In this paper, some aspects related to the random generation of artificial instances are studied, and the assumption that states that sampling uniformly at random in the space of parameters is equivalent to sampling uniformlyat random inThe space of functions is elaborated.

### Gray-box optimization and factorized distribution algorithms: where two worlds collide

- Computer ScienceArXiv
- 2017

The general question of using problem structure in EAs is analyzed focusing on confronting work done in gray-box optimization with related research accomplished in FDAs, and it is claimed that these two characterizations collide and compete at the time of providing a coherent framework to investigate this type of algorithms.

### The Minimization of Public Facilities With Enhanced Genetic Algorithms Using War Elimination

- Computer ScienceIEEE Access
- 2019

An enhanced version of the genetic algorithm based on war elimination and migration operations is presented, which overcomes the well-known shortcoming of GAs when the population becomes gradually more and more similar, which results in a diversity decrease which leads to a sub-optimal local minimum.

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