Assortment Optimization under Heteroscedastic Data

We study assortment problems under the Marginal Exponential Model (MEM) with deterministic demand. We show that optimal solutions to such assortment problems can be efficiently determined under some mild conditions, and provide a simple approach that finds near optimal solutions when these conditions fail. Furthermore, we improve the existing MEM parameter estimation method given by … Read more

Divisive heuristic for modularity density maximization

In this paper we consider a particular method of clustering for graphs, namely the modularity density maximization. We propose a hierarchical divisive heuristic which works by splitting recursively a cluster into two new clusters by maximizing the modularity density, and we derive four reformulations for the mathematical programming model used to obtain the optimal splitting. … Read more