An approximation method for the P-median problem: A bioinspired tabu search and variable neighborhood search partitioning approach

Abstract

The bioinspired systems are presented as a set of models that are based on the behavior of some biological systems and how act. These models can be expressed in data mining and operations research where clustering is a recurrent technique used to solve the P-median and territorial design problems. At this point, we have solved the P-median problem with a partitioning approach with bioinspired aspects and Variable Neighborhood Search (VNS). In this work we have improved the basic VNS search strategy and we present a bioinspired partitioning algorithm with optimization by Tabu Search (TS). This clustering-partitioning problem under a bioinspired connotation has been proposed after observing some characteristics in common between clustering and human behavior during conflict situations, where some characteristics have been modeled accordingly. Finally we present our progress from our VNS implementation to our TS proposal.