Hands-On Genetic Algorithms with Python by Eyal Wirsansky is a new book which explores the world of genetic algorithms to solve search, optimization, and AI-related tasks, and improve machine ...

Quantum computers of the future hold promise for solving complex problems more quickly than ordinary computers. For example, they can factor large numbers exponentially faster than classical ...

Lysa Porth, Jeffrey Pai, Milton Boyd, A Portfolio Optimization Approach Using Combinatorics With a Genetic Algorithm for Developing a Reinsurance Model, The Journal of Risk and Insurance, Vol. 82, No.

Evolutionary optimization (EO) is a technique for finding approximate solutions to difficult or impossible numeric optimization problems. In particular, EO can be used to train a neural network. EO is ...

One of the most fundamental processes in all of biology is the spontaneous organization of cells into clusters that divide ...

In order to maximize the efficiency, a heuristic search based algorithm - Genetic Algorithm (GA) is used. The problem is formulated as a multi-objective optimization problem (MOOP) where overall ...

Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue ...

Quantum approximate optimization algorithm can be implemented using Rydberg atoms 14 Apr 2022 Quantum optimization team: from left to right are Kilian Ender, Clemens Dlaska, Wolfgang Lechner, Rick van ...