Herein, we cover the application of multi- and many-objective optimization methods, particularly those based on Evolutionary Computation and Machine Learning techniques, to enlighten their potential ...

It has been shown that non-convex optimization problems can be transformed into better structured problems through monotonic transformations of the objective functions. This work proposes Pairing ...

Multi-objective optimization (MOO) is a branch of optimization that deals with problems that have more than one objective function to optimize simultaneously. For example, if you are building a ...

Elekta Monaco (v5.1) treatment planning system provides multi-criteria optimization based on Pareto Front function optimization, which is effective in improving the equivalent uniform dose and tumor ...

For efficient multi-start optimization, TPTD leverages a target point defined in the objective space, which plays a critical role in shaping the scalarized function.

1. Effective decision-making in environmental management requires the consideration of multiple objectives that may conflict. Common optimization methods use weights on the multiple objectives to ...