A family tree and a summary table based on this classification are presented to provide a concrete overview of metaheuristic algorithms developed from the 1960s to the present. Last but not least, some promising research directions and open issues are given to discuss the future of metaheuristic ...
In this chapter, we presented an overview of metaheuristic algorithms applied in several problems of phase equilibrium calculation, particularly in: (1) the prediction of reactive azeotropy (mainly when two reactive azeotropes occur); and (2) the calculation of dew point pressures in systems with...
Notably, it outperforms several other metaheuristic algorithms, making it a valuable addition to the field of optimization techniques. This paper provides a notable contribution to the ever-evolving landscape of optimization algorithms, offering promising applications for challenging real-world problems. Al...
The complexity of practical real-world problems usually makes it almost impossible to fully search the solution space, and in such cases, metaheuristic approaches can be utilized as high-level procedures providing a sufficient solution to the optimization problem at hand [39]. There are many ...
The first one frames the ACO approach in current trends of research on metaheuristic algorithms for combinatorial optimization; the second outlines current research within the ACO framework, reporting recent results obtained on different problems, while the third part focuses on a particular research ...
In many applications, the complexity and nonlinearity of the problems require novel and alternative approaches to problem solving. In recent years, nature-inspired algorithms, especially those based on swarm intelligence, have become popular, due to the simplicity and flexibility of such algorithms. Her...
摘要原文 Ant Colony Optimization (ACO) is a metaheuristic that is inspired by the pheromone trail laying and following behavior of some ant species. Artificial ants in ACO are stochastic solution construction procedures that build candidate solutions for the problem instance under concern by exploiting...
Research in metaheuristics for global optimization problems are currently experiencing an overload of wide range of available metaheuristic-based solution
The Particle swarm optimization (PSO) algorithm is a population-based intelligent stochastic search technique encouraged from the intrinsic manner of bee s... BW Haider,AhmadJamil,RH Tayyab - 《International Journal of Applied Metaheuristic Computing》 被引量: 0发表: 2020年 An Overview of Cluster ...
characteristics of lithium-ion batteries that must be considered in the algorithms applied to the BMS. Thus, the set of concepts examined in this review supports the need to evolve the devices and develop new methods for estimating the SoC, which is increasingly more accurate and faster. This ...