African Buffalo Optimization

Odili, Julius Beneoluchi; Kahar, Mohd Nizam Mohmad

doi:10.15282/ijsecs.2.2016.3.0014

Cited by 19 publications

(6 citation statements)

References 34 publications

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“…A new optimization methodology which is presented and termed as the African Buffalo Optimization by Odili et al, (2016). One of the endangered wild species that cattle in Africa is the African buffalos, it is set to find the rainy weather forecasts in various parts of Africa as it is mostly in mobile tracking.…”

Section: Methodsmentioning

confidence: 99%

Chaotic African Buffalo Optimization Based Efficient Key Mechanism in Categorized Sensor Networks

Arunkumar¹

2020

IJEAT

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In recent days, Wireless Sensor Network (WSN) can be used to monitor the circumstances of various movable objects and several processes such as friendly forces monitoring, biological attack detection, fire detection and so on its applications are extended. To make all these applications reliable and secure, it is necessary to use cryptographic processes. The security of the whole network is depending on the strength of a generated key, the algorithm decides the size of the key handling and processing. In this research, a secure efficient key management scheme is proposed with the help of Chaotic African Buffalo Optimization (CABO) for wireless sensor networks. The evaluation of this method is made with the objective to improve the security strength and reduce the cost of resource. The traditional methods called genetic algorithm and an evolutionary algorithm named as Particle Swarm Optimization (PSO) is compared to verify the proposed scheme.

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Section: Methodsmentioning

confidence: 99%

Chaotic African Buffalo Optimization Based Efficient Key Mechanism in Categorized Sensor Networks

Arunkumar¹

2020

IJEAT

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“…To design an effective hybrid algorithm, there is the need for a thorough grasp of the algorithms' components and employ the concept of component grafting [26]. In this study, first, a new t-way suite test generation strategy is proposed; called Buffalo Strategy (BS) based on the ABO algorithm [27,28]. The ABO has been improved to obtain several hybridization variants of the original ABO.…”

Section: Hybrid African Buffalo Optimization For T-way Test Suite Gen...mentioning

confidence: 99%

“…Please note that λ is a random number. The ABO algorithm searching strategy is governed by the equations [31]:…”

Section: Hybrid African Buffalo Optimization For T-way Test Suite Gen...mentioning

confidence: 99%

African Buffalo Optimization Algorithm Based T-Way Test Suite Generation Strategy for Electronic-Payment Transactions

Odili¹,

Nasser

Ahmad

et al. 2021

Proceedings of International Conference on Emerging Technologies and Intelligent Systems

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The use of meta-heuristics in Combinatorial Interaction Testing (CIT) is becoming more and more popular due to their effectiveness and efficiency over the traditional methods especially in authenticating electronic payment (epayment) transactions. Concomitantly, over the past two decades, there has been a rise both in the development of metaheuristics and their application to diverse theoretical and practical areas including CIT in e-payments. In the implementation of t-way strategies (the t is used to represent the interaction strength), mixed results have been reported; some very exciting but, in other cases, the performance of metaheuristics has been, to say the least, below par. This mixed trend has led many researchers to explore alternate ways of improving the effectiveness and efficiency of metaheuristics in CIT, hence this study. It must be emphasized, however, that available literature indicates that no particular metaheuristic testing strategy has had consistent superior performance over the others in diverse testing environments and configurations. The need for effectiveness, therefore, necessitates the need for algorithm hybridization to deploy only the component parts of algorithms that have been proven to enhance overall search capabilities while at the same time eliminating the demerits of particular algorithms in the hybridization procedure. In this paper, therefore, a hybrid variant of the African Buffalo Optimization (ABO) algorithm is proposed for CIT. Four hybrid variants of the ABO are proposed through a deliberate improvement of the ABO with four algorithmic components. Experimental procedures indicate that the hybridization of the ABO with these algorithmic components led to faster convergence and greater effectiveness superior to the outcomes of existing techniques, thereby placing the algorithm among the best when compared with other methods/techniques.

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“…Using the /waaa/ (explore) and the /maaa/ (exploit) calls, the African buffalos are able to optimize their search for good grazing fields out of starving locations into very satisfying ones [25]. The African Buffalo Optimization (ABO) algorithm is presented in Figure 5 [26].…”

Section: African Buffalo Optimization and Pid Tuningmentioning

confidence: 99%

African Buffalo Optimization Algorithm for Tuning Parameters of a PID Controller in Automatic Voltage Regulators

Odili

Kahar

Noraziah³

2016

International Journal of Simulation: Systems, Science &Amp; Technology

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In this paper, we present the African Buffalo Optimization (ABO) approach for the metaheuristic tuning of the Proportional, Integral & Derivative (PID) Controller parameters of Automatic Voltage Regulators in electrical power generation and transmission. ABO simulates the movement of African Buffalos as they migrate from place to place all over Africa in search of grazing pastures. The buffalos use just two basic vocalizations, namely the waaa and the maaa to organize the entire herd in their migration and search for food and water. Though a recently-designed algorithm, the ABO has been effective and efficient in solving a number of search optimization problems. The highpoints of the ABO include its use of few parameters, constant interactions among the buffalos and the deployment of the exploration and exploitations mechanisms of the algorithm in every iteration. The simulation outcome of the application of ABO to tune the parameters of a PID-Controller parameters of Automatic Voltage Regulators has been very competitive when compared similar outcomes of other metaheuristics tuners: BFO-PID, PSO-PID, GA-PID, PID-PSO, PID Tuner and ACO-PID.

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African Buffalo Optimization

Cited by 19 publications

References 34 publications

Chaotic African Buffalo Optimization Based Efficient Key Mechanism in Categorized Sensor Networks

Chaotic African Buffalo Optimization Based Efficient Key Mechanism in Categorized Sensor Networks

African Buffalo Optimization Algorithm Based T-Way Test Suite Generation Strategy for Electronic-Payment Transactions

African Buffalo Optimization Algorithm for Tuning Parameters of a PID Controller in Automatic Voltage Regulators

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