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

The team's findings further revealed that, while multi-objective evolutionary algorithms hold significant potential, they still struggle with low search efficiency.

Tan Liu, Qinyun Yuan, Lina Wang, Yonggang Wang, Nannan Zhang, Multi-objective optimization for oil-gas production process based on compensation model of comprehensive energy consumption using improved ...

The Multi-Query Optimization (MQO) problem is a class of data-intensive problems that are NP-hard, and it has applications in many fields such as database query optimization, machine learning ...

According to Theyr CEO and Founder David Young, T-VOS differs from earlier generation voyage management software in its adoption of multi-objective algorithmic techniques.

Simultaneous Reduction of Engine Emissions and Fuel Consumption Using Genetic Algorithms and Multi-Dimensional Spray and Combustion Modeling ...

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