Real-valued functions of complex arguments violate the Cauchy-Riemann conditions and, consequently, do not have Taylor series expansion. Therefore, optimization methods based on derivatives cannot be ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

Neural network (NN) has been tentatively combined into multi-objective genetic algorithms (MOGAs) to solve the optimization problems in physics. However, the computationally complex physical ...

“We live in a nonlinear world,” said Dr. Oliver Bastert, vice president of product management for FICO Platform. “That means clear, consistent, ‘linear’ relationships between variables don’t always ...

Researchers have developed a new, data-driven machine-learning technique that speeds up software programs used to solve complex optimization problems that can have millions of potential solutions.

A quantum computer can solve optimization problems faster than classical supercomputers, a process known as "quantum advantage" and demonstrated by a USC researcher in a paper recently published in ...

Overview Quantum systems evaluate countless supply chain variables simultaneously, helping organizations solve complex ...

A framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a new study. A ...

Utilities optimizing their distribution systems today often are addressing challenges in addition to Volt/VAR optimization. VVO on distribution systems with a growing variety of DER and load sources ...