Tensor networks enable researchers to tackle quantum physics problems previously thought to be solvable only by quantum computers. Credit: Lucy Reading-Ikkanda/Simons Foundation By applying a 1980s ...
Why do algorithms keep showing us content we claim not to want? The answer isn’t manipulation—it’s conflict between our ...
Our genetic heritage is not a blueprint or an algorithm, as many biologists have imagined, but something else entirely.
Abstract: Small to medium sized transportation and logistics companies are usually constrained by limited computing and IT professional resources on implementing an efficient parallel metaheuristic ...
This is a modern implementation of the Hybrid Genetic Search (HGS) with Advanced Diversity Control of [1], specialized to the Capacitated Vehicle Routing Problem (CVRP). This algorithm has been ...
Many common mental health disorders, including depression and anxiety, are associated with a tendency to internalize problems or, in other words, to direct feelings inwards instead of expressing them ...
Abstract: The Traveling Salesman Problem (TSP), a classic combinatorial optimization problem, has been extensively studied for many years. Recently, the Multi-solution Traveling Salesman Problem ...
Combinatorial optimization problems in fields like logistics, finance, and computational biology are increasingly approaching the computational limits of classical methods. Many of these problems are ...
Gene Expression Programming (GEP) is a popular and established evolutionary algorithm for automatic generation of computer programs and mathematical models. It has found wide applications in symbolic ...
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Reactor radiation-shielding optimization methods are proposed by combining many-objective evolutionary algorithms with particle-transport calculation software that can optimize the reactor ...
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