Abstract: Real world objective functions often produce two types of uncertain output: noise and imprecision. While there is a distinct difference between both types, most optimization algorithms treat ...

However, they can suffer from having a slow convergence speed. This paper proposes a new indicator-based multi-objective optimization algorithm, namely, the multi-objective shuffled frog leaping ...

Genetic algorithm is widely used in multi-objective mechanical structure optimization. In this paper, a genetic algorithm-based optimization method for ladle refractory lining structure is proposed.

Recently, evolutionary multi-objective optimization (EMO) algorithms have received a surge of attention in microgrid applications. Due to the population-based, black-box search/optimization ...

The study introduces an AI-driven approach to concrete mix design, optimizing for strength and sustainability while reducing ...

Multi-objective optimization algorithms are used to solve optimization problems with multiple conflicting objectives. These algorithms aim to find a set of optimal solutions that represent a trade-off ...

Consequently, this paper aims to address these shortcomings of SBOA by proposing a multi-strategy improved Sparrow and Eagle Optimization Algorithm (HS-SBOA) to enhance its performance in complex ...

Tomoaki Takagi, Keiki Takadama, and Hiroyuki Sato: Supervised Multi-objective Optimization Algorithm Using Estimation, Proc. of IEEE Congress on Evolutionary Computation (CEC2022), pp. 1--8, 2022. DOI ...