Search Results for author:
Found 9 papers, 6 papers with code
jsdp: a Java Stochastic DP Library
Stochastic Dynamic Programming is a branch of Stochastic Programming that takes a "functional equation" approach to the discovery of optimal policies.
Declarative Statistics
In this work we introduce declarative statistics, a suite of declarative modelling tools for statistical analysis.
The Dynamic Bowser Routing Problem
Motivated by a practical case study elicited in the context of a project we recently conducted at Crossrail, we introduce the Dynamic Bowser Routing Problem.
Optimization and Control
Stochastic Constraint Programming as Reinforcement Learning
Reinforcement Learning (RL) extends Dynamic Programming to large stochastic problems, but is problem-specific and has no generic solvers.
The BIN_COUNTS Constraint: Filtering and Applications
We show that BIN_COUNTS can be employed to develop a decomposition for the $\chi^2$ test constraint, a new statistical constraint that we introduce in this work.
Statistical Constraints
We introduce statistical constraints, a declarative modelling tool that links statistics and constraint programming.
A unified modeling approach for the static-dynamic uncertainty strategy in stochastic lot-sizing
In this paper, we develop mixed integer linear programming models to compute near-optimal policy parameters for the non-stationary stochastic lot sizing problem under Bookbinder and Tan's static-dynamic uncertainty strategy.
Optimization and Control Systems and Control Probability
Piecewise linear approximations of the standard normal first order loss function
When the random variable of interest is normally distributed, the first order loss function can be easily expressed in terms of the standard normal cumulative distribution and probability density function.
Optimization and Control Probability
Confidence-based Reasoning in Stochastic Constraint Programming
In this work we introduce a novel approach, based on sampling, for finding assignments that are likely to be solutions to stochastic constraint satisfaction problems and constraint optimisation problems.
