Announcement of the Quantum Information Recursive Optimization (QIRO) algorithm positions MicroAlgo as a leader in innovative quantum computing solutions for combinatorial optimization problems ...

For simple optimization problems, finding the best solution is just a matter of arithmetic. But the real-world questions that interest mathematicians and scientists are rarely simple. In 1847, the ...

When using an evolutionary algorithm you need to define a method for the specific problem being optimized. In some situations you might need to pass additional information to the Solver class. For ...

The goal of a combinatorial optimization problem is to find a set of distinct integer values that minimizes some cost function. The most famous example is the Traveling Salesman Problem (TSP). There ...

The researchers say that the innovations in math and algorithms they have developed are as critical as the machine itself in solving optimization problems. The novel type of algorithm being used in ...

Applying the Quantum Approximate Optimization Algorithm to the Tail-Assignment Problem. Physical Review Applied , 2020; 14 (3) DOI: 10.1103/PhysRevApplied.14.034009 Cite This Page : ...

When people program new deep learning AI models — those that can focus on the right features of data by themselves — the vast majority rely on optimization algorithms, or optimizers, to ensure ...

MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), today announced the development of an innovative hybrid algorithm that combines the advantages of classical and quantum computing to ...