• Structural Engineering and Mechanics
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• v.86 no.2
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• pp.197-209
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• 2023

In the case of designing control devices in a building, reliance on experimental formulation or engineering concepts without using optimization algorithms leads to non-optimal solutions or design parameters, which makes the use of control devices costly and unreasonable. The optimization algorithms are capable of identifying the required number of parameters for a specific design problem, however, this process is difficult and inefficient in dealing with some specific optimal design processes. This paper aims to introduce an upgraded version of the salp swarm algorithm to handle some engineering design. The performance of the new upgraded algorithm is tested using some benchmark test functions as well as a six-story benchmark building equipped with semi-active MR dampers. The simulation results show that the proposed algorithm can be successfully applied to get an optimal design of the MR dampers in the building.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2225-2239
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• 2021

To assist in data collection, the use of a mobile sink has been widely suggested in the literature. Due to the limited sensor node's storage capacity, this manner to collect data induces huge latencies and drop packets. Their buffers will be overloaded and lead to network congestion. Recently, a new bio-inspired optimization algorithm appeared. Researchers were inspired by the swarming mechanism of salps and thus creating what is called the Salp Swarm Algorithm (SSA). This paper improves the sink mobility to enhance energy dissipation, throughput, and convergence speed by imitating the salp's movement. The new approach, named the Mobile Sink based on Modified Salp Swarm Algorithm (MSSA), is approved in a heterogeneous Wireless Sensor Network (WSN) data collection. The performance of the MSSA protocol is assessed using several iterations. Results demonstrate that our proposal surpass other literature algorithms in terms of lifespan and throughput.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1142-1166
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• 2020

Salp Swarm Algorithm (SSA) is a new nature-inspired swarm optimization algorithm that mimics the swarming behavior of salps navigating and foraging in the oceans. SSA has been proved to enable to avoid local optima and enhance convergence speed benefiting from the adaptive nonlinear mechanism and salp chains. In this paper, visual tracking is considered to be a process of locating the optimal position through the interaction between leaders and followers in successive images. A novel SSA-based tracking framework is proposed and the analysis and adjustment of parameters are discussed experimentally. Besides, the qualitative analysis and quantitative analysis are performed to demonstrate the tracking effect of our proposed approach by comparing with ten classical tracking algorithms. Extensive comparative experimental results show that our algorithm has good performance in visual tracking, especially for abrupt motion tracking.

• Earthquakes and Structures
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• v.18 no.6
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• pp.719-730
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• 2020

Recently, population based optimization algorithms are developed to deal with a variety of optimization problems. In this paper, the salp swarm algorithm (SSA) is dramatically enhanced and a new algorithm is named Enhanced Salp Swarm Algorithm (ESSA) which is effectively utilized in optimization problems. To generate the ESSA, an opposition-based learning and merit function methods are added to standard SSA to enhance both exploration and exploitation abilities. To have a clear judgment about the performance of the ESSA, firstly, it is employed to solve some mathematical benchmark test functions. Next, it is exploited to deal with engineering problems such as optimally designing the benchmark buildings equipped with multiple tuned mass damper (MTMD) under earthquake excitation. By comparing the obtained results with those obtained from other algorithms, it can be concluded that the proposed new ESSA algorithm not only provides very competitive results, but also it can be successfully applied to the optimal design of the MTMD.

• Earthquakes and Structures
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• v.17 no.1
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• pp.63-73
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• 2019

This paper studies damage detection as an optimization problem. A new objective function based on changes in natural frequencies, and Natural Frequency Vector Assurance Criterion (NFVAC) was developed. Due to their easy and fast acquisition, natural frequencies were utilized to detect structural damages. Moreover, they are sensitive to stiffness reduction. The method presented here consists of two stages. Firstly, Finite Element Model (FEM) is updated. Secondly, damage severities and locations are determined. To minimize the proposed objective function, a new bio-inspired optimization algorithm called salp swarm was employed. Efficiency of the method presented here is validated by three experimental examples. The first example relates to three-story shear frame with two single damage cases in the first story. The second relates to a five-story shear frame with single and multiple damage cases in the first and third stories. The last one relates to a large-scale eight-story shear frame with minor damage case in the first and third stories. Moreover, the performance of Salp Swarm Algorithm (SSA) was compared with Particle Swarm Optimization (PSO). The results show that better accuracy is obtained using SSA than using PSO. The obtained results clearly indicate that the proposed method can be used to determine accurately and efficiently both damage location and severity in multi-story shear frames.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1225-1232
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• 2023

The ¹⁸⁰W is the lightest isotope of Tungsten with small abundance ratio. It is slightly radioactive (α decay), with an extremely long half-life. Its separation is possible by non-conventional single withdrawal cascades. The ¹⁸⁰W is used in radioisotopes production and study of metals through gamma-ray spectroscopy. In this paper, single withdrawal cascade model is developed to evaluate multicomponent separation in non-conventional transient cascades, and available experimental results are used for validation. Numerical studies for separation of ¹⁸⁰W in a transient single withdrawal cascade are performed. Parameters affecting the separation and equilibrium time of cascade such as number of stages, cascade arrangements, feed location and flow rate for a fixed number of gas centrifuges (GC) are investigated. The Salp Swarm Algorithm (SSA) as a bio-inspired optimization algorithm is applied as a novel method to minimize the feed consumption to obtain desired concentration in the collection tank. Examining different cascade arrangements, it is observed in arrangements with more stages, the separation is further efficient. Based on the obtained results, with increasing feed flow rate, for fixed product concentration, the cascade equilibrium time decreases. Also, it is shown while the feed location is the farthest stage from the collection tank, the separation and cascade equilibrium time are well-organized. Finally, using SSA optimal parameters of the cascade is calculated, and optimal arrangement to produce 5 gr of ¹⁸⁰W with 90% concentration in the tank, is proposed.

• Steel and Composite Structures
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• v.29 no.1
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• pp.139-149
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• 2018

In this paper a new multi-step damage detection approach is provided. In the first step, condensed modal residual vector based indicator (CMRVBI) has been proposed to locate the suspected damaged elements of structures that have rotational degrees of freedom (DOFs). The CMRVBI is a new indicator that uses only translational DOFs of the structures to localize damaged elements. In the next step, salp swarm algorithm is applied to quantify damage severity of the suspected damaged elements. In order to assess the performance of the proposed approach, a numerical example including a three-layer square laminated composite plate is studied. The numerical results demonstrated that the proposed CMRVBI is effective for locating damage, regardless of the effect of noise. The efficiency of proposed approach is also compared during both steps. The results demonstrate that in noisy condition, the damage identification approach is capable for the studied structure.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3291-3300
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• 2023

Recently molybdenum alloys have been introduced as accident tolerating materials for cladding of fuel rods. Molybdenum element has seven stable isotopes with different neutron absorption cross section used in various fields, including nuclear physics and radioisotope production. This study presents separation approaches for all intermediate isotopes of molybdenum element by squared-off cascades using a newly developed numerical code with Salp Swarm Algorithm (SSA) optimization algorithm. The parameters of cascade including feed flow rate, feed entry stage, cascade cut, input feed flow rate to gas centrifuges (GCs), and cut of the first stage are optimized to maximize both isotope recovery and cascade capacity. The squared off and squared cascades are studied, and the efficiencies are compared. The results obtained from the optimization showed that for the selected squared off cascade, Mo⁹⁴ in four separation steps, Mo⁹⁵ in five steps, Mo⁹⁶ in six steps, Mo⁹⁷ in seven steps, and Mo⁹⁸ in two steps are separated to the desired concentrations. The highest recovery factor is obtained 63% for Mo⁹⁴ separation and lowest recovery factor is found 45% for Mo⁹⁵.

• Coupled systems mechanics
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• v.13 no.1
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• pp.1-19
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• 2024

The effectiveness of coupling with a bolted rim is assessed in this research using a newly designed optimization algorithm. The current study, which is provided here, evaluates 10 contemporary metaheuristic approaches for enhancing the coupling with bolted rim design problem. The algorithms used are particle swarm optimization (PSO), crow search algorithm (CSA), enhanced honeybee mating optimization (EHBMO), Harmony search algorithm (HSA), Krill heard algorithm (KHA), Pattern search algorithm (PSA), Charged system search algorithm (CSSA), Salp swarm algorithm (SSA), Big bang big crunch optimization (B-BBBCO), Gradient based Algorithm (GBA). The contribution of the paper isto optimize the coupling with bolted rim problem by comparing these 10 algorithms and to find which algorithm gives the best optimized result. These algorithm's performance is evaluated statistically and subjectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1317-1341
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• 2021

Nowadays, the Internet of Things (IoT) is adopted to enable effective and smooth communication among different networks. In some specific application, the Wireless Sensor Networks (WSN) are used in IoT to gather peculiar data without the interaction of human. The WSNs are self-organizing in nature, so it mostly prefer multi-hop data forwarding. Thus to achieve better communication, a cross-layer routing strategy is preferred. In the cross-layer routing strategy, the routing processed through three layers such as transport, data link, and physical layer. Even though effective communication achieved via a cross-layer routing strategy, energy is another constraint in WSN assisted IoT. Cluster-based communication is one of the most used strategies for effectively preserving energy in WSN routing. This paper proposes a Bio-inspired cross-layer routing (BiHCLR) protocol to achieve effective and energy preserving routing in WSN assisted IoT. Initially, the deployed sensor nodes are arranged in the form of a grid as per the grid-based routing strategy. Then to enable energy preservation in BiHCLR, the fuzzy logic approach is executed to select the Cluster Head (CH) for every cell of the grid. Then a hybrid bio-inspired algorithm is used to select the routing path. The hybrid algorithm combines moth search and Salp Swarm optimization techniques. The performance of the proposed BiHCLR is evaluated based on the Quality of Service (QoS) analysis in terms of Packet loss, error bit rate, transmission delay, lifetime of network, buffer occupancy and throughput. Then these performances are validated based on comparison with conventional routing strategies like Fuzzy-rule-based Energy Efficient Clustering and Immune-Inspired Routing (FEEC-IIR), Neuro-Fuzzy- Emperor Penguin Optimization (NF-EPO), Fuzzy Reinforcement Learning-based Data Gathering (FRLDG) and Hierarchical Energy Efficient Data gathering (HEED). Ultimately the performance of the proposed BiHCLR outperforms all other conventional techniques.