jsdp: a Java Stochastic DP Library
Not on the map. Why?
Abstract (arXiv)
Stochastic Programming is a framework for modelling and solving problems of decision making under uncertainty. Stochastic Dynamic Programming is a branch of Stochastic Programming that takes a "functional equation" approach to the discovery of optimal policies. By leveraging constructs - lambda expressions, functional interfaces, collections and aggregate operators - implemented in Java to operationalise the MapReduce framework, jsdp provides a general purpose library for modelling and solving Stochastic Dynamic Programs.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 21 references that are in the map. First posted on arXiv 20 Sep 2022.
Builds on
2 of 21 references.
References · 2
- 2017The Dynamic Bowser Routing Problemcited by 1
- 2019Efficient Stochastic Programming in Juliacited by 1
Built on by
Not cited yet.