Discrete self-organizing migration algorithm and p-location problems

Location problems optimization by a self-organizing multiagent approach

The Facility Location Problem (FLP) requires locating facilities in order to optimize some performance criteria. This problem occurs in many practical settings where facilities provide a service, such as the location of plants, bus-stops, fire stations, etc. Particularly, we deal with the continuous version of location problem where facilities have to be located in an Euclidean plane. This pape...

Stochastic p-robust location problems

The two most widely considered measures for optimization under uncertainty are minimizing expected cost and minimizing worst-case cost or regret. In this paper, we present a novel robustness measure that combines the two objectives by minimizing the expected cost while bounding the relative regret in each scenario. In particular, the models seek the minimum-expected-cost solution that is p-robu...

Self-organizing map algorithm and distortion measure

We study the statistical meaning of the minimization of distortion measure and the relation between the equilibrium points of the SOM algorithm and the minima of the distortion measure. If we assume that the observations and the map lie in a compact Euclidean space, we prove the strong consistency of the map which almost minimizes the empirical distortion. Moreover, after calculating the deriva...

Discrete location problems with push-pull objectives

Closest assignment constraints in discrete location problems

The objective of this paper is to identify the most promising sets of closest assignment constraints in the literature of Discrete Location Theory, helping the authors in the field to model their problems when clients must be assigned to the closest plant inside an Integer Programming formulation. In particular, constraints leading to weak Linear Programming relaxations should be avoided if no ...