African Buffalo Optimization for Global Optimization

Odili, Julius Beneoluchi; Ahmad, Nesar

doi:10.18520/cs/v114/i03/627-636

Cited by 11 publications

(5 citation statements)

References 22 publications

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“…We performed the tests using 3, 5 and 10 dimensions. Additionally, we considered such two-dimensional test functions, as Ackley [32], Matyas [36], Eggholder [37] and Booth [36] functions, defined in Table 1 as f 5 , f 6 , f 7 and f 8 , respectively. The Michalewicz [32] function f 9 was tested with 2, 5 and 10 dimensions.…”

Section: Numerical Experimentsmentioning

confidence: 99%

Research and Study of the Hybrid Algorithms Based on the Collective Behavior of Fish Schools and Classical Optimization Methods

Demidova

Gorchakov

2020

Algorithms

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Inspired by biological systems, swarm intelligence algorithms are widely used to solve multimodal optimization problems. In this study, we consider the hybridization problem of an algorithm based on the collective behavior of fish schools. The algorithm is computationally inexpensive compared to other population-based algorithms. Accuracy of fish school search increases with the increase of predefined iteration count, but this also affects computation time required to find a suboptimal solution. We propose two hybrid approaches, intending to improve the evolutionary-inspired algorithm accuracy by using classical optimization methods, such as gradient descent and Newton’s optimization method. The study shows the effectiveness of the proposed hybrid algorithms, and the strong advantage of the hybrid algorithm based on fish school search and gradient descent. We provide a solution for the linearly inseparable exclusive disjunction problem using the developed algorithm and a perceptron with one hidden layer. To demonstrate the effectiveness of the algorithms, we visualize high dimensional loss surfaces near global extreme points. In addition, we apply the distributed version of the most effective hybrid algorithm to the hyperparameter optimization problem of a neural network.

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Section: Numerical Experimentsmentioning

confidence: 99%

Research and Study of the Hybrid Algorithms Based on the Collective Behavior of Fish Schools and Classical Optimization Methods

Demidova

Gorchakov

2020

Algorithms

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“…African Buffalo Optimization technique devised by Odili and Kahar in 2015 provides an effective algorithm without all these limitations, still maintaining a real good accuracy level. [34] This algorithm is based on the intelligent behavior of wild buffalo with symbiotic support and grazing area search capabilities of the African buffalos. [35] The algorithm is based on the three features of wild African buffalo, Good memory, peculiar sounds of 'Waa' and 'Maa' to communicate about danger or safe grazing areas and a sort of voting in a group whenever a dispute arises between the leader and group members.…”

Section: Figure-11 Ftir Of Wco Biodiesel E Biodiesel Production Yielmentioning

confidence: 99%

Hybrid Response Surface Method African Buffalo Optimization Technique for Ultrasonic Production of Biodiesel from Waste Cooking Oil using Li doped CaO Nan o catalyst

Kumar*,

Gupta

2020

IJITEE

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In the current era, there is an increasing emphasis on green fuels for a clean environment. Authors in this work have tried to devise an innovative method to optimize ultrasonic production of biodiesel from used cooking oil, using composite technique combining Response surface Methodology and African Buffalo optimization. In this research work, heterogeneous catalyst Lithium doped CaO has been obtained from a new natural source by high-temperature thermal decomposition of Musa Balbisiana root ash and tested its Conversion efficiency for conversion of waste cooking oil into methyl esters. It was observed that the catalyst is really effective for the production of biodiesel from even high Free Fatty Acid waste cooking oil. For optimization of production parameters authors have used ABO complemented with RSM to maximize the biodiesel production yield. The maximum biodiesel yield of 96.67% was achieved using ABO which is about 15% higher than provided by RSM which is 81.01%. The highest biodiesel yield of 96.67 % is obtained at 15:1 Molar Ratio with 3.5% catalyst wt. percent, 60 Degree C Temp. in 45 Minutes with an error of 2.5 % in yield prediction by ABO. The work may be utilized by industries and researchers to use ultrasonic reactors optimally to extract better biodiesel volume in very short time instead of presently used slow mechanical stirring tank reactors.

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“…Some of the popular optimization algorithms in literature include Genetic Algorithm, Particle Swarm Optimization, Sine-Cosine optimization algorithm 4 , Simulated Annealing, Hill Climbing, Tabu Search, Hybrid Whale Nelder Mead algorithm 5 , Great Deluge Algorithm etc 6 . These algorithms have been applied to solve several optimization problems ranging from vehicle routing, network routing, constrained truss optimization problems 7 , job scheduling, collision-avoidance 8 , mobile ad-hoc networks, tuning PID parameters of Automatic Voltage Regulators 9 , sports and examination timetabling 10 , test suite optimization 11 , energy enhancement 12 , global optimization problems 5 , automobile connecting rod components etc 13 with good results.…”

Section: Introductionmentioning

confidence: 99%

Stochastic process and tutorial of the African buffalo optimization

Odili¹,

Ahmad

Alkazemi

et al. 2022

Sci Rep

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This paper presents the data description of the African buffalo optimization algorithm (ABO). ABO is a recently-designed optimization algorithm that is inspired by the migrant behaviour of African buffalos in the vast African landscape. Organizing their large herds that could be over a thousand buffalos using just two principal sounds, the /maaa/ and the /waaa/ calls present a good foundation for the development of an optimization algorithm. Since elaborate descriptions of the manual workings of optimization algorithms are rare in literature, this paper aims at solving this problem, hence it is our main contribution. It is our belief that elaborate manual description of the workings of optimization algorithms make it user-friendly and encourage reproducibility of the experimental procedures performed using this algorithm. Again, our ability to describe the algorithm’s basic flow, stochastic and data generation processes in a language so simple that any non-expert can appreciate and use as well as the practical implementation of the popular benchmark Rosenbrock and Shekel Foxhole functions with the novel algorithm will assist the research community in benefiting maximally from the contributions of this novel algorithm. Finally, benchmarking the good experimental output of the ABO with those of the popular, highly effective and efficient Cuckoo Search and Flower Pollination Algorithm underscores the ABO as a worthy contribution to the existing body of population-based optimization algorithms

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African Buffalo Optimization for Global Optimization

Cited by 11 publications

References 22 publications

Research and Study of the Hybrid Algorithms Based on the Collective Behavior of Fish Schools and Classical Optimization Methods

Research and Study of the Hybrid Algorithms Based on the Collective Behavior of Fish Schools and Classical Optimization Methods

Hybrid Response Surface Method African Buffalo Optimization Technique for Ultrasonic Production of Biodiesel from Waste Cooking Oil using Li doped CaO Nan o catalyst

Stochastic process and tutorial of the African buffalo optimization

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