Optimization problems often involve situations in which the user's goal is to minimize and/or maximize not a single objective function, but several, usually conflicting, functions simultaneously. Such ...

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

Abstract: In combinatorial optimization problems, traditional optimization algorithms are often difficult to efficiently find the global optimal solution. This paper studies the application of genetic ...

ABSTRACT: Ahead of the Internet of Things and the emergence of big data, the interest of research is today focused on radio access and the process of optimizing it or increasing its capacity and ...

Abstract: The genetic algorithm is one of the most commonly used metaheuristics due to its adaptability to various types of problems. However, its implementation can be challenging because of the ...

This report explores the use of genetic algorithms for optimizing financial quantitative trading strategies. Genetic algorithms are a type of evolutionary computation method that mimics the natural ...

The operation of the power grid is closely related to meteorological disasters. Changes in meteorological conditions may have an impact on the operation and stability of the power system, leading to ...

(www.nag.com; www.nag.co.uk; www.nag-gc.com; www.nag-j.co.jp) Worldwide electronic engineers seeking the most appropriate way to solve difficult optimization problems can get easy to follow ...