A New Approach to the Stock Location Assignment Problem by Multidimensional Scaling and Seriation

The problem of the best stock location assignment in a warehouse has a fundamental role while optimising picking activities. In the present paper, this problem has been faced by considering seven variables to compute similarity between items. In this context, the problem of the choice of the most adequate similarity (or dissimilarity) measure between units while applying Multidimensional Scaling (MDS), has been examined. Besides the right metric, the possibility of applying a Seriation algorithm has been also considered. By using both MDS and seriation not just a single target can be considered, but we are able to manage with a plenty of variables; on the contrary with techniques used in literature, proper to Operational Research, just a single variable is under observation, and therefore just a single goal can be achieved. A wide discussion on the results is presented.