Robust variant of artificial bee colony (JA-ABC4b) algorithm

Sulaiman, Noorazliza; Mohamad–Saleh, Junita; Abro, Abdul Ghani

doi:10.1504/ijbic.2017.085896

Cited by 9 publications

(3 citation statements)

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“…The proposed algorithm was verified on twenty-two benchmark functions. Sulaiman et al [19] presented a robust ABC to balance exploitation and exploration. Experiments on 27 test functions and economic environmental dispatch (EED) problems show the effectiveness of the approach.…”

Section: A Brief Review Of Abcmentioning

confidence: 99%

An ABC Algorithm with Recombination

You¹,

Ma²,

Liu³

et al. 2018

INT J COMPUT COMMUN

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Artificial bee colony (ABC) is an efficient swarm intelligence algorithm, which has shown good exploration ability. However, its exploitation capacity needs to be improved. In this paper, a novel ABC variant with recombination (called RABC) is proposed to enhance the exploitation. RABC firstly employs a new search model inspired by the updating equation of particle swarm optimization (PSO). Then, both the new search model and the original ABC model are recombined to build a hybrid search model. The effectiveness of the proposed RABC is validated on ten famous benchmark optimization problems. Experimental results show RABC can significantly improve the quality of solutions and accelerate the convergence speed.

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Section: A Brief Review Of Abcmentioning

confidence: 99%

An ABC Algorithm with Recombination

You¹,

Ma²,

Liu³

et al. 2018

INT J COMPUT COMMUN

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“…This optimization problem was first revealed by Carpentier in 1962 and it relates to security and economic dispatch of a power system (Li, 2013;Yan et al, 2020). As important as it is, many researchers, academics and scientists have gathered to develop various search strategies to optimize power system's operation and planning (Sulaiman et al, 2017). Attempts have been made to solve RPO problem using various classical methods such as linear programming, Newton method, and interior point based on stochastic and heuristics techniques (Rahman et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Reactive Power Optimization Using New Enhanced Whale Optimization Algorithm

Rahman

Mohamad–Saleh

Sulaiman

2022

International Journal of Applied Metaheuristic Computing

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The standard Whale Optimization Algorithm (WOA) involves exploitation and exploration operations which require to be balanced for improved performance. This paper suggests a new enhanced WOA to improve the convergence speed and enhance the global optimum by balancing exploitation and exploration processes. New stages have been suggested at the hunting stages of the WOA to increase the exploitation capability. The performance of the modified algorithm has been analyzed on few commonly used test functions and Reactive Power Optimization (RPO) problem. The numerical studies have shown that the proposed WOA variant has outperformed other compared optimization algorithms in terms of global optimum and convergence speed.

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“…Cluster-head node selection is a complex optimization problem that should consider the node location and node residual energy. A biological heuristic algorithm is an effective method for solving this optimization problem, such as via standard particle swarm optimization (PSO) [18][19][20][21], ant colony optimization [22][23][24][25][26][27], cuckoo search (CS) [28][29][30][31][32], and artificial bee colony algorithm (ABC) [33][34][35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Optimal LEACH Protocol with Improved Bat Algorithm in Wireless Sensor Networks

2019

KSII TIIS

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A low-energy adaptive clustering hierarchy (LEACH) protocol is a low-power adaptive cluster routing protocol which was proposed by MIT's Chandrakasan for sensor networks. In the LEACH protocol, the selection mode of cluster-head nodes is a random selection of cycles, which may result in uneven distribution of nodal energy and reduce the lifetime of the entire network. Hence, we propose a new selection method to enhance the lifetime of network, in this selection function, the energy consumed between nodes in the clusters and the power consumed by the transfer between the cluster head and the base station are considered at the same time. Meanwhile, the improved FTBA algorithm integrating the curve strategy is proposed to enhance local and global search capabilities. Then we combine the improved BA with LEACH, and use the intelligent algorithm to select the cluster head. Experiment results show that the improved BA has stronger optimization ability than other optimization algorithms, which the method we proposed (FTBA-TC-LEACH) is superior than the LEACH and LEACH with standard BA (SBA-LEACH). The FTBA-TC-LEACH can obviously reduce network energy consumption and enhance the lifetime of wireless sensor networks (WSNs).

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Robust variant of artificial bee colony (JA-ABC4b) algorithm

Cited by 9 publications

References 0 publications

An ABC Algorithm with Recombination

An ABC Algorithm with Recombination

Reactive Power Optimization Using New Enhanced Whale Optimization Algorithm

Optimal LEACH Protocol with Improved Bat Algorithm in Wireless Sensor Networks

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