Using MPI (2nd ed.): portable parallel programming with the message-passing interface
Using MPI (2nd ed.): portable parallel programming with the message-passing interface
A Heuristic for Moment-Matching Scenario Generation
Computational Optimization and Applications
Feature Article: Optimization for simulation: Theory vs. Practice
INFORMS Journal on Computing
Generating Scenario Trees for Multistage Decision Problems
Management Science
Parallel Programming in C with MPI and OpenMP
Parallel Programming in C with MPI and OpenMP
Portfolio and investment risk analysis on global grids
Journal of Computer and System Sciences
A decision support system for strategic asset allocation
Decision Support Systems
An advanced system for portfolio optimisation
International Journal of Grid and Utility Computing
Hi-index | 7.29 |
A crucial issue for addressing decision-making problems under uncertainty is the approximate representation of multivariate stochastic processes in the form of scenario tree. This paper proposes a scenario generation approach based on the idea of integrating simulation and optimization techniques. In particular, simulation is used to generate outcomes associated with the nodes of the scenario tree which, in turn, provide the input parameters for an optimization model aimed at determining the scenarios' probabilities matching some prescribed targets. The approach relies on the moment-matching technique originally proposed in [K. Hoyland, S.W. Wallace, Generating scenario trees for multistage decision problems, Manag. Sci. 47 (2001) 295-307] and further refined in [K. Hoyland, M. Kaut, S.W. Wallace, A heuristic for moment-matching scenario generation, Comput. Optim. Appl. 24 (2003) 169-185]. By taking advantage of the iterative nature of our approach, a parallel implementation has been designed and extensively tested on financial data. Numerical results show the efficiency of the parallel algorithm and the improvement in accuracy and effectiveness.