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

Alireza Sahebgharani, MULTI-OBJECTIVE LAND USE OPTIMIZATION THROUGH PARALLEL PARTICLE SWARM ALGORITHM, Journal of Urban and Environmental Engineering, Vol. 10, No. 1 (January to June 2016), pp. 42-49 ...

Adaptive optimization algorithms promise better results and deeper insight into why certain designs perform better than ...

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

Milling is a prevalent machining technique employed in various industries for the production of metallic and non-metallic components. This article focuses on the optimization of cutting parameters for ...

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

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 ...

Machine learning algorithms are gaining popularity in the hydrologic sciences. These algorithms often require tuning hyperparameters to tailor their performance to a specific purpose. Often these ...