Distances in the well known fuzzy c-means algorithm of Bezdek (1973) are measured by the squared Euclidean distance. Other distances have been used as well in fuzzy clustering. For example, Jajuga (1991) proposed to use the L_1-distance and Bobrowski and Bezdek (1991) also used the...

We address the dynamic lot sizing problem for systems with product returns. The demand and return amounts are deterministic over the finite planning horizon. Demands can be satisfied by manufactured/procured new items, but also by remanufactured returned items. The objective is to determine...

In this article we describe reinforcement learning, a machine learning technique for solving sequential decision problems. We describe how reinforcement learning can be combined with function approximation to get approximate solutions for problems with very large state spaces. One such problem...

Closed Loop Supply Chains include operations for physical collection of end-of-use products, selection based on their configuration and/or condition and decision making for reuse, remanufacturing or recycling. Uncertainty factors regarding the time, place of origin, and status of returns...

The notion of transit function is introduced to present a unifying approach for results and ideas on intervals, convexities and betweenness in graphs and posets. Prime examples of such transit functions are the interval function I and the induced path function J of a connected graph. Another...

In this chapter we use a simulation experiment to examine whether the seasonal adjustment methods Census X12-ARIMA and TRAMO/SEATS effectively remove seasonality properties from time series data, while preserving other features like the stochastic trend. As data generating processes we use a...

The Majority Strategy for finding medians of a set of clients on a graph can be relaxed in the following way: if we are at v, then we move to a neighbor w if there are at least as many clients closer to w than to v (thus ignoring the clients at equal distance from v and w). The graphs on which...

We create a hedonic price model for house prices for six geographical submarkets in the Netherlands. Our model is based on a recent data mining technique called boosting. Boosting is an ensemble technique that combines multiple models, in our case decision trees, into a combined prediction....

Two-mode clustering is a relatively new form of clustering that clusters both rows and columns of a data matrix. To do so, a criterion similar to k-means is optimized. However, it is still unclear which optimization method should be used to perform two-mode clustering, as various methods may...

A response style denotes a certain mapping of latent preferences to a rating scale that is common among a certain group of individuals. For example, individuals from the same country may assign high ratings to the majority of objects regardless of the specific preferences for the objects. The...