Abstract Stochastic Fractal Search (SFS) is a new and original meta-heuristic search (MHS)
algorithm with strong foundations. As with many other MHS methods, there are problems in …

Metaheuristic algorithms are currently being studied in depth by many scholars, and it is an
important task to improve the learning and adaptive capabilities of the algorithms so that …

In this article, a new metaheuristic algorithm called Siberian Tiger Optimization (STO) is
designed to deal with optimization applications. The fundamental inspiration of STO is the …

In the optimization of constrained type problems, the main difficulty is the elimination of the
constraint violations in the evolutionary search process. Evolutionary algorithms are …

Marine predator algorithm adopts the policy of optimal encounter rate in biological
interaction between predator and prey, inspired by the Lévy and Brownian motions …

This paper presents the improved version of the Lévy Flight Distribution (LFD) algorithm for
solving real-valued numerical optimization problems. In the proposed algorithm, the Fitness …

This study proposes a robust method to improve the search performance of multi-objective
evolutionary algorithms (MOEAs) using a Pareto-based archiving mechanism and a …

The search domain of meta-heuristic algorithms is always constantly changing, which make
it difficult to adapt the diverse optimization issues. To overcome above issue, an evolutionary …

This article has four main objectives. These are: to develop the dynamic fitness-distance
balance (d FDB) selection method for meta-heuristic search algorithms, to develop a strong …

Abstract The recently introduced Marine Predators Algorithm (MPA) exhibits competitive
performance in solving optimization problems. However, it often prematurely converges due …