Machine-learning-assisted de novo design of organic molecules and polymers: opportunities and challenges
Organic molecules and polymers have a broad range of applications in biomedical,
chemical, and materials science fields. Traditional design approaches for organic molecules …
chemical, and materials science fields. Traditional design approaches for organic molecules …
[PDF][PDF] 进化多目标优化算法研究
公茂果[1， 焦李成[1， 杨咚咚[1， 马文萍[1 - 软件学报, 2009 - jos.org.cn
进化多目标优化主要研究如何利用进化计算方法求解多目标优化问题, 已经成为进化计算领域的
研究热点之一. 在简要总结2003 年以前的主要算法后, 着重对进化多目标优化的最新进展进行了 …
研究热点之一. 在简要总结2003 年以前的主要算法后, 着重对进化多目标优化的最新进展进行了 …
A mini-review on preference modeling and articulation in multi-objective optimization: current status and challenges
Evolutionary multi-objective optimization aims to provide a representative subset of the
Pareto front to decision makers. In practice, however, decision makers are usually interested …
Pareto front to decision makers. In practice, however, decision makers are usually interested …
Pareto set learning for expensive multi-objective optimization
Expensive multi-objective optimization problems can be found in many real-world
applications, where their objective function evaluations involve expensive computations or …
applications, where their objective function evaluations involve expensive computations or …
[图书][B] Evolutionary algorithms for solving multi-objective problems
CAC Coello - 2007 - Springer
Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …
solution has been a challenge to researchers for a long time. Despite the considerable …
An introduction and survey of estimation of distribution algorithms
M Hauschild, M Pelikan - Swarm and evolutionary computation, 2011 - Elsevier
Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that
explore the space of potential solutions by building and sampling explicit probabilistic …
explore the space of potential solutions by building and sampling explicit probabilistic …
Combining model-based and genetics-based offspring generation for multi-objective optimization using a convergence criterion
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 …
evolutionary algorithms can be greatly enhanced if the regularity in the distribution of Pareto …
Research on evolutionary multi-objective optimization algorithms
公茂果， 焦李成， 杨咚咚， 马文萍 - Journal of software, 2009 - jos.org.cn
进化多目标优化主要研究如何利用进化计算方法求解多目标优化问题, 已经成为进化计算领域的
研究热点之一. 在简要总结 2003 年以前的主要算法后, 着重对进化多目标优化的最新进展进行 …
研究热点之一. 在简要总结 2003 年以前的主要算法后, 着重对进化多目标优化的最新进展进行 …
Foundations of machine learning for low-temperature plasmas: methods and case studies
Abstract Machine learning (ML) and artificial intelligence have proven to be an invaluable
tool in tackling a vast array of scientific, engineering, and societal problems. The main …
tool in tackling a vast array of scientific, engineering, and societal problems. The main …