In this work we present an overview of the most prominent population-based algorithms and
the methodologies used to extend them to multiple objective problems. Although not exact in …

摘要分布估计算法是进化计算领域新兴起的一类随机优化算法, 是当前国际进化计算领域的研究
热点. 分布估计算法是遗传算法和统计学习的结合, 通过统计学习的手段建立解空间内个体分布 …

To approximate the Pareto front, most existing multiobjective evolutionary algorithms store
the nondominated solutions found so far in the population or in an external archive during …

Over the last decade, a variety of evolutionary algorithms (EAs) have been proposed for
solving multiobjective optimization problems. Especially more recent multiobjective …

In our previous work [1], it has been shown that the performance of multi-objective
evolutionary algorithms can be greatly enhanced if the regularity in the distribution of Pareto …

Multiobjective Evolutionary Algorithms and Applications provides comprehensive treatment
on the design of multiobjective evolutionary algorithms and their applications in domains …

The field of natural computing has been the focus of a substantial research effort in recent
decades. One particular strand of this concerns the development of computational …

In recent years, several researchers have concentrated on using probabilistic models in
evolutionary algorithms. These Estimation Distribution Algorithms (EDA) incorporate …

There are four primary goals of this dissertation. First, design a competent optimization
algorithm capable of learning and exploiting appropriate problem decomposition by …

The concept of optimization—finding the extrema of a function that maps candidate'solutions'
to scalar values of 'quality'—is an extremely general and useful idea that can be, and is …