Erratum to: A copula-based heuristic for scenario generation

Erratum to: A copula-based heuristic for scenario generation

In this section, we present a heuristic for the bivariate case of the average-deviation problem. Just like the MIP formulation (9) from the previous section, the heuristic works on the ranks of the copula and uses the difference between the cdfs as a measure of distance between the sample and the target. It is based on the observation from Eq. (2) that the rank cdf Cr (i, j) depends only on poi...

A copula-based heuristic for scenario generation

In most practical applications of stochastic programming, we have to approximate the probability distribution of the stochastic parameters by a discrete distribution, i.e. a list of realizations (scenarios) and their probabilities. The process of generating this discrete distribution is usually referred to as ‘scenario generation’. As with any other approximation, the quality of the scenarios i...

A Heuristic for Moment-Matching Scenario Generation

Copula-Based Approach to Synthetic Population Generation

Generating synthetic baseline populations is a fundamental step of agent-based modeling and simulation, which is growing fast in a wide range of socio-economic areas including transportation planning research. Traditionally, in many commercial and non-commercial microsimulation systems, the iterative proportional fitting (IPF) procedure has been used for creating the joint distribution of indiv...

A Heuristic Approach to Distributed Generation Source Allocation for Electrical Power Distribution Systems

The recent trends in electrical power distribution system operation and management are aimed at improving system conditions in order to render good service to the customer. The reforms in distribution sector have given major scope for employment of distributed generation (DG) resources which will boost the system performance. This paper proposes a heuristic technique for allocation of distribut...