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Multi-objective optimisation using evolutionary algorithms constitutes a powerful computational framework that addresses complex problems involving conflicting objectives.
Adaptive optimization algorithms promise better results and deeper insight into why certain designs perform better than ...
Second, the conversion to a single-objective optimization problem involves additional constraints. Third, since most real-world goal programming problems involve nonlinear criterion functions, the ...
Computational optics integrates optical hardware and algorithms, enhancing imaging capabilities through joint optimization ...
Considering the undesirable characteristics of the balance shaft, such as cost, weight, friction, and noise, as well as dynamically inappropriate mass unbalancing method, this research proposes ...
In an era where autonomous systems demand pinpoint accuracy, navigation algorithms face a tough trade-off between precision ...
Beyond Trial and Error: A Ghanaian contribution to metaheuristic classification and its implications
In the fast-evolving fields of artificial intelligence, operations research, and computational intelligence, metaheuristics ...
MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO) announced today the launch of their latest classifier auto-optimization technology based on Variational Quantum Algorithms (VQA). This ...
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