Multi-objective optimisation using evolutionary algorithms constitutes a powerful computational framework that addresses complex problems involving conflicting objectives.

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 ...

Other algorithms, such as the Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), break the optimization problem into smaller sub-problems, each representing a weighted combination ...

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 ...

Computational optics integrates optical hardware and algorithms, enhancing imaging capabilities through joint optimization ...

In the fast-evolving fields of artificial intelligence, operations research, and computational intelligence, metaheuristics ...

In an era where autonomous systems demand pinpoint accuracy, navigation algorithms face a tough trade-off between precision ...

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 ...