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 ...

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 ...

G. Gary Wang, Songqing Shan, Design Space Reduction for Multi-Objective Optimization and Robust Design Optimization Problems, SAE Transactions, Vol. 113, Section 5: JOURNAL OF MATERIALS AND ...

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

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

The addition of Simultaneous Multi-Objective Optimization is part of John Galt Solutions' ongoing, composable journey to expand optimization capabilities, empowering customers to make smarter ...