Michal Kaut This paper shows how to implement long-term storage in the multi-horizon modelling paradigm, expanding the range of problems this approach is applicable to. The presented implementation is based on the HyOpt optimization model, but the ideas should be transferable also to other models implementing the multi-horizon approach. We illustrate the effects of several different formulations … Read more
In this paper, we present a method for generating scenarios by selection from historical data. We start with two models for a univariate single-period case and then extend the better-performing one to the case of selecting sequences of multivariate data. We then test the method on data series for wind- and solar-power generation in Scandinavia. … Read more
Sometimes, the best available information about an uncertain future is a single forecast. On the other hand, stochastic-programming models need future data in the form of scenario trees. While a single forecast does not provide enough information to construct a scenario tree, a forecast combined with historical data does—but none of the standard scenario-generation methods … Read more
Infrastructure-planning models are challenging because of their combination of different time scales: while planning and building the infrastructure involves strategic decisions with time horizons of many years, one needs an operational time scale to get a proper picture of the infrastructure’s performance and profitability. In addition, both the strategic and operational levels are typically subject … Read more
This paper presents a new heuristic for generating scenarios for two-stage stochastic programs. The method uses copulas to describe the dependence between the marginal distributions, instead of the more common correlations. The heuristic is then tested on a simple portfolio-selection model, and compared to two other scenario-generation methods. Citation Published in Computational Management Science, 11 … Read more