SEATTLE, Oct. 18, 2018 (GLOBE NEWSWIRE) -- Bias Intelligence Inc., a data science company focused on the end-to-end delivery of solutions to the most challenging process optimization problems facing global companies, today announced the publishing of a co-authored research paper titled Auction Bidding Methods for Multiagent Consensus Optimization in Supply–Demand Networks.  Published on the IEEE Xplore® Digital Library as part of the IEEE Robotics and Automation Letters (RA-L), the research paper was developed in partnership with the University of Washington mechanical engineering department and addressed some of the most complex problems facing the practical implementation of multi-agent consensus optimization algorithms in commercial scenarios.  The paper co-authors include Niyousha Rahimi, Department of Mechanical Engineering, University of Washington; Jundi Liu, Department of Industrial and Systems Engineering, University of Washington; Andrey Shishkarev, Bias Intelligence Inc.; Ilya Buzytsky, Bias Intelligence Inc.; and Ashis G. Banerjee, Department of Industrial and Systems Engineering and Department of Mechanical Engineering, University of Washington.  

"I am incredibly excited to announce the release of this academic paper which proposes a new way to approach multi-agent consensus optimization,” said Ilya Buzytsky, Chief Executive Officer of Bias Intelligence.  “At Bias our goal is to advance the system optimization industry by leaps and bounds using modern technologies.  With the ability to 'scale out' computational power using cloud-based platforms like Microsoft Azure and Amazon Web Services, we can address many of the limitations of legacy optimization software packages that rely on linear programming and require enormous amounts of time and computational burden.  The idea of multi-agent consensus will show up everywhere in the future:  autonomous car and truck networks, energy grid management, robotics planning and distribution, drone swarm optimization and virtually all types of system disruption management.  We couldn’t be prouder to bring these algorithms to life in our forthcoming products and services and thank the University of Washington for all their support.”

To review and download the research paper, please visit https://ieeexplore.ieee.org/document/8463627, and to learn more about Bias Intelligence, please visit http://biasintelligence.com.

About Bias Intelligence
Bias Intelligence is a data science company focused on the end-to-end delivery of solutions to the most challenging process optimization problems facing global companies today. Bias Intelligence delivers these solutions through a set of packaged software offerings combined with an advanced understanding of big data platforms in the industry today. We enable customers to unlock the true potential of their data by helping them gather insight and make decisions in order to optimize their business processes.  Bias Intelligence was founded in 2015 and is headquartered in Seattle, Washington. Learn more at http://biasintelligence.com.

Contact Information

Contact:
Ilya Buzytsky
Chief Executive
ilya@biasintelligence.com