English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Pro

Presents the zaia usage as premium feature

ZAIA

Presents AI Discovery search usage as a premium feature

AI Discovery

Presents AI Discovery explain and summary usage as a premium feature

Content Analysis

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Presents the pdf analysis as premium feature

PDF Analysis

1500 Top-up

3000 Top-up

Zendy Basic

2500 Top-up

Zendy Unlimited

Presents the access of premium content as premium feature

Premium Content

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.

REGION-BASED HEURISTICS FOR AN ITERATIVE PARTITIONING PROBLEM IN MULTIAGENT SYSTEMS