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

Two of artificial intelligence’s most powerful yet fundamentally different tools are quietly merging, and a new open-access scientometric review has, for the first time, mapped exactly how fast, how b ...

Optimization problems rarely have a single right answer. In engineering design, scheduling, and machine learning, decision ...

Evolutionary algorithms, inspired by natural selection and genetics, offer versatile frameworks for exploring complex design spaces where traditional analytical methods falter. By iteratively evolving ...

Expensive optimization problem (EOP) refers to the problem that requires expensive or even unaffordable costs to evaluate candidate solutions, which widely exist in many significant real-world ...

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Researchers from Tokyo Metropolitan University have used an evolutionary algorithm to identify optimal shapes for ultra-thin, bio-inspired corrugated airfoils, the two-dimensional cut-throughs of ...

Researchers from Tokyo Metropolitan University have used an evolutionary algorithm to identify optimal shapes for ultra-thin ...