The traditional golden jackal optimization algorithm (GJO) has slow convergence speed,
insufficient accuracy, and weakened optimization ability in the process of finding the optimal …

In this paper, a novel multi-objective grey wolf optimizer (MOGWO) based on multiple search
strategies (ie, adaptive chaotic mutation strategy, boundary mutation strategy, and elitism …

This paper introduces a novel hybrid optimization algorithm called MoSSE by combining the
features of Multi-objective Spotted Hyena Optimizer (MOSHO), Salp Swarm Algorithm (SSA) …

In recent years, the cuckoo search (CS) algorithm has been successfully applied to single-
objective optimization problems. But in real life, most optimization problems are multi …

Recently, several meta-heuristics and evolutionary algorithms have been proposed for
tackling optimization problems. Such methods tend to suffer from degraded performance …

Swarm intelligence optimization methods have steadily gained popularity as a solution to
multi-objective optimization issues in recent years. Their study has garnered a lot of attention …

This paper presents an efficient cooperative multi-populations swarm intelligence algorithm
based on the Harris Hawks optimization (HHO) algorithm, named CMPMO-HHO, to solve …

Abstract In this paper, Multi-Objective Harris Hawks Optimization (MOHHO) is proposed
based on strengthened dominance relation (SRD) to solve multi-objective optimization …

In order to further improve the performance of the Multi-objective Evolutionary Algorithm
Based on Decomposition (MOEA/D) in solving multi-objective optimization problems, this …

In this paper, a multi-objective version of the Harris Hawk Optimizer algorithm (HHO) is
proposed, which is called Multi-Objective Harris Hawk Optimization (MOHHO). In the …