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...

For electricity market participants trading in sequential markets with differences in price levels and risk exposure, it is relevant to analyze the potential of coordinated bidding. We consider a Nordic power producer who engages in the day-ahead spot market and the hour-ahead balancing market....

In this paper, we propose multi-stage stochastic linear programming for asset-liability management under time-varying investment opportunities. We use a first-order unrestricted vector autoregressive process to model predictability in the asset returns and the state variables, where - additional...

This paper addresses the shipment planning problem with random processing times in intermodal logistics via transfer ports. Shipment activities are divided into two groups according to regional settings. Activity processing times in region A are assumed to be random while those in region B are...

<Para ID="Par1">Data for optimization problems often comes from (deterministic) forecasts, but it is naïve to consider a forecast as the only future possibility. A more sophisticated approach uses data to generate alternative future scenarios, each with an attached probability. The basic idea is to estimate...</para>

Decision making about portfolio selection problem under uncertainty is very important and critical, so it is rational and necessary to use ideas of a DM who is proficient in stochastic problems. For example, the Goal Attainment Programming (GAP) is one of the methods in priori category that...

This paper investigates the farm level impacts of multiple peril yield and revenue insurance in an expected value-variance framework. The analysis is conducted using stochastic simulation jointly with numerical optimisation. Simulation is used to compute the means and variances of revenues as...