Researchers at Yazd University developed a binary version of the Puma Optimization Algorithm that achieved 91.53 percent ...

CSA, a multi-strategy upgrade of the Crow Search Algorithm that outperforms ten competing optimizers on benchmarks, four ...

Numerous real-world applications involve large-scale multi-objective optimization problems (LSMOPs) with hundreds or even thousands of decision variables. Although multi-objective evolutionary ...

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, researchers ...

Computer-generated holography (CGH) provides an approach to digitally modulate a given wavefront. This technology, partly inherited from optical holography and partly advanced by the progress of ...

The traveling salesman problem is considered a prime example of a combinatorial optimization problem. Now a Berlin team led by theoretical physicist Prof. Dr. Jens Eisert of Freie Universität Berlin ...

Right now, quantum computers are small and error-prone compared to where they’ll likely be in a few years. Even within those limitations, however, there have been regular claims that the hardware can ...

WiMi's proposed technical solution has its core innovations concentrated on the deep integration of model-based reinforcement learning algorithms and hierarchical circuit structures, constructing a ...

Dr. James McCaffrey of Microsoft Research uses full code samples to detail an evolutionary algorithm technique that apparently hasn't been published before. The goal of a combinatorial optimization ...

Since the very first days of computer science — a field known for its methodical approach to problem-solving — randomness has played an important role. The first program to run on the world’s first ...