What is the fastest route to take, the most efficient employee schedule, or the financial portfolio with the least amount of risk? Optimization is the science of finding the best solutions among many possibilities.
Optimization: The Science of Making Better Decisions
Making the best possible decisions is critical to the success of most businesses. This is particularly relevant today because companies have access to a large amount of high-quality data and they are interested in using this data to drive their decision making. The science of optimization can help businesses find the best solution among all possible solutions to maximize their performance and minimize their costs.
Scaling Overhead of Locality Reduction in Binary Optimization Problems
By Elisabetta Valiante, Maritza Hernandez, Amin Barzegar, & Helmut G. Katzgraber
Recently, there has been considerable interest in solving optimization problems by mapping these onto a binary representation, sparked mostly by the use of quantum annealing machines. Such binary representation is reminiscent of a discrete physical two-state system, such as the Ising model. As such, physics-inspired techniques—commonly used in fundamental physics studies—are ideally suited to solve optimization problems in a binary format…
Solve intractable industrial optimization problems today. Prepare your business for a quantum computing revolution tomorrow.What is 1Qloud™The 1Qloud™ platform is a computational bridge that connects intractable industry problems to novel quantum-inspired optimization solutions that utilize the most advanced hardware. Our unique hardware-agnostic approach enables operations researchers, data...
Long-Short Minimum Risk Parity Optimization Using a Quantum or Digital Annealer
By Gili Rosenberg & Maxwell Rounds
In portfolio optimization, many weight allocation strategies result in long-only positions. We show how it is possible to formulate and solve an optimization problem that assigns a direction (long or short) to each weight allocation, such that the variance is minimized or maximized…
Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer
By Maliheh Aramon, Gili Rosenberg, Elisabetta Valiante, Toshiyuki Miyazawa, Hirotaka Tamura, & Helmut G. Katzgraber
The Fujitsu Digital Annealer (DA) is designed to solve fully connected quadratic unconstrained binary optimization (QUBO) problems. It is implemented on application-specific CMOS hardware and currently solves problems of up to 1024 variables….