NEJan 19, 2014
Evolutionary Optimization for Decision Making under Uncertainty
arXiv:1401.4696v12 citations
Originality Synthesis-oriented
AI Analysis
It provides an overview for researchers and practitioners interested in heuristic approaches to optimization under uncertainty, but it is incremental as it is a survey article.
This paper surveys evolutionary optimization techniques for solving stochastic programming problems, both single-stage and multi-stage, as a method for decision-making under uncertainty.
Optimizing decision problems under uncertainty can be done using a variety of solution methods. Soft computing and heuristic approaches tend to be powerful for solving such problems. In this overview article, we survey Evolutionary Optimization techniques to solve Stochastic Programming problems - both for the single-stage and multi-stage case.