In this paper, an enhanced version of the salp swarm algorithm (SSA) for global optimization problems was developed. Two improvements have been proposed: (i) Diversification SSA population referred as $$_{std}$$ , (ii) parameters are tuned using a self-adaptive technique-based genetic (GA) $$_{GA-tuner}$$ . The novelty developing is to enhance its performance through balancing search exploratio...

The Salp Swarm Algorithm (SSA) outperforms well-known algorithms such as particle swarm optimizers and grey wolf in complex optimization challenges. However, like most meta-heuristic algorithms, SSA suffers from slow convergence stagnation the best local solution. In this study, a algorithm is combined with escaping operator (LEO) to overcome some inherent limitations of original SSA. SSALEO no...

Salp Sürü Algoritması (SSA) son dönem sürü zekâsı algoritmalarından olup, basit yapılıdır ve kullanımı oranı artan bir algoritmadır. Kullanım oranındaki artışın en önemli sebebi, bu algoritmanın problem çözmede gösterdiği başarıdır. Buna karşın, SSA algoritmasının performansı türleri değiştikçe kötüleşebilmektedir. Bu çalışma, durumu ele almakta olup global optimizasyon için Cauchy (caSSA) adın...

This article presents a new method based on meta-heuristic algorithm for maximum power point tracking (MPPT) in photovoltaic systems. In this method, the SALP Swarm Algorithm (SSA) is used instead of classic methods such as Perturb and Observe (P&O) method. value duty cycle optimally determined an optimization problem by SSA order to track power. The objective function maximizing output sys...

Simulated annealing (SA) algorithm is a popular intelligent optimisation algorithm, but its efficiency is unsatisfactory. To improve its efficiency, this paper presents a swarm SA (SSA) algorithm by exploiting the learned knowledge from searching history. In SSA, a swarm of individuals run SA algorithm collaboratively. Inspired by ant colony optimisation (ACO) algorithm, SSA stores knowledge in...

In this paper, we propose a modified hybrid Salp Swarm Algorithm (SSA) and Aquila Optimizer (AO) named IHSSAO for UAV path planning in complex terrain. The primary logic of the proposed is to enhance performance AO by introducing leader mechanism SSA, tent chaotic map, pinhole imaging opposition-based learning strategy. Firstly, map utilized substitute randomly generated initial population orig...

In order to solve the problem that conventional tracker is not adapted abrupt motion, a tracking algorithm based on improved salp swarm (ISSA) was proposed. Visual considered be process of locating optimal position through interaction between leaders and followers in successive images. Firstly, adaptive mechanism leader follower introduced into original (SSA) balance exploitation exploration al...

(1) Background: Feature selection is the biggest challenge in feature-rich sentiment analysis to select best (relevant) feature set, offer information about relationships between features (informative), and be noise-free from high-dimensional datasets improve classifier performance. This study aims propose a binary version of metaheuristic optimization algorithm based on Swarm Intelligence, nam...

Using recycled aggregate in concrete is one of the best ways to reduce construction pollution and prevent exploitation natural resources provide needed aggregate. However, aggregates affect mechanical properties concrete, but existing information on subject less than what industry needs. Compressive strength, other hand, most important property concrete. Therefore, having predictive models requ...

Abstract There are many design problems need to be optimized in various fields of engineering, and most them belong the NP-hard problem. The meta-heuristic algorithm is one kind optimization method provides an effective way solve Salp swarm (SSA) a nature-inspired that mimics mathematically models behavior slap nature. However, similar algorithms, traditional SSA has some shortcomings, such as ...