Big Data Optimization Book

Today, individuals and organizations are changing the world with Big Data. Data has become a new source of immense economic and social value.

Hence formulation of optimization problems with unprecedented sizes (millions or billions of variables) is inevitable. This book aims to introduce novel optimization algorithms and codes capable of working in the Big Data setting as the classical optimization algorithms are not designed to scale to instances of this size.

Advances in data mining and analytics and the massive increase in computing power and data storage capacity have expanded, by orders of magnitude, the scope of information available to businesses, government, and individuals. This book is providing state of art on Big Data Optimization for both academics and practitioners interested in Business Analytics Optimization to address current developments and challenges in Big Data, and to benefit society, industry, academia, and government. The intent is to cover the theory, research, development, and applications of Big Data, as embedded in the fields of mathematics, engineering, computer science, physics, economics, business, management and life sciences.

This book will be published by Springer in the series "Studies in Big Data". The aim of this series is to publish new developments and advances in the various areas of Big Data.

We wish to invite you to contribute to this edited book. We hope that you will be able to accept our invitation.

At this stage, we invite you to submit [by August 31, 2014] a 1-2 page chapter proposal clearly explaining the goals and objectives of your proposed chapter.

Selection process and timeline
Since timeliness is crucial to the success of this editorial project, we would assume the following schedule:

selectionand timeline

Please click here to submit your proposal.
(Alternatively, please email your proposal to


See also

Call for Paper Presentation