Region-Based Heuristics for an Iterative Partitioning Problem in Multiagent Systems

Abstract

Load balancing or access point selection in wireless networks both are problems where a large set of particles repeatedly has to be partitioned on another set of objects. In general this partitioning problem involves multiple contrary objectives. Due to the large number of particles a decentralized approach should be favored. In this work, such an iterative multi-objective optimization problem is modeled as multiagent system. We propose a local solution technique based on regions and some special coordination media. Agents select target objects based on the region they are in. Different region types are considered and a local heuristic is developed. We show the general potential of regions and experimentally analyze different approaches. All approaches are able to provide high quality solutions.