Hybrid Bat Algorithm with Artificial Bee Colony

2014 ◽  
pp. 45-55 ◽  
Author(s):  
Trong-The Nguyen ◽  
Jeng-Shyang Pan ◽  
Thi-Kien Dao ◽  
Mu-Yi Kuo ◽  
Mong-Fong Horng
Keyword(s):  
Artificial Bee Colony ◽  
Bat Algorithm ◽  
Bee Colony

scholarly journals Hybrid ABC-BAT for Solving Short-Term Hydrothermal Scheduling Problems

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 551 ◽  
Author(s):  
Smarajit Ghosh ◽  
Manvir Kaur ◽  
Suman Bhullar ◽  
Vinod Karar
Keyword(s):  
Hybrid Algorithm ◽  
Artificial Bee Colony ◽  
Optimal Allocation ◽  
Bat Algorithm ◽  
Scheduling Problems ◽  
Short Term ◽  
Hydrothermal Scheduling ◽  
Hybrid Techniques ◽  
Bee Colony ◽  
The Cost

The main objective of short-term hydrothermal scheduling is the optimal allocation of the hydro and thermal generating units, so that the total cost of thermal plants can be minimized. The time of operation of the functioning units are considered to be 24 h. To achieve this objective, the hybrid algorithm combination of Artificial Bee Colony (ABC) and the BAT algorithm were applied. The swarming behavior of the algorithm searches the food source for which the objective function of the cost is to be considered; here, we have used two search algorithms, one to optimize the cost function, and another to improve the performance of the system. In the present work, the optimum scheduling of hydro and thermal units is proposed, where these units are acting as a relay unit. The short term hydrothermal scheduling problem was tested in a Chilean system, and confirmed by comparison with other hybrid techniques such as Artificial Bee Colony–Quantum Evolutionary and Artificial Bee Colony–Particle Swarm Optimization. The efficiency of the proposed hybrid algorithm is established by comparing it to these two hybrid algorithms.

Hybridizing bat algorithm with artificial bee colony for combined heat and power economic dispatch

2018 ◽  
Vol 72 ◽  
pp. 189-217 ◽  
Author(s):  
R. Murugan ◽  
M.R. Mohan ◽  
C. Christober Asir Rajan ◽  
P. Deiva Sundari ◽  
S. Arunachalam
Keyword(s):  
Artificial Bee Colony ◽  
Economic Dispatch ◽  
Bat Algorithm ◽  
Combined Heat And Power ◽  
Bee Colony ◽  
Power Economic

A New Stochastic Optimization Approach — Dolphin Swarm Optimization Algorithm

2016 ◽  
Vol 15 (02) ◽  
pp. 1650011 ◽  
Author(s):  
Wang Yong ◽  
Wang Tao ◽  
Zhang Cheng-Zhi ◽  
Huang Hua-Juan
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Artificial Bee Colony ◽  
Bat Algorithm ◽  
Global Optimum ◽  
The Other ◽  
Optimization Approach ◽  
Swarm Optimization ◽  
Bee Colony ◽  
Fast Convergence Rate

A novel nature-inspired swarm intelligence (SI) optimization is proposed called dolphin swarm optimization algorithm (DSOA), which is based on mimicking the mechanism of dolphins in detecting, chasing after, and preying on swarms of sardines to perform optimization. In order to test the performance, the DSOA is evaluated against the corresponding results of three existing well-known SI optimization algorithms, namely, particle swarm optimization (PSO), bat algorithm (BA), and artificial bee colony (ABC), in the terms of the ability to find the global optimum of a range of the popular benchmark functions. The experimental results show that the proposed optimization seems superior to the other three algorithms, and the proposed algorithm has the performance of fast convergence rate, and high local optimal avoidance.

PERFORMANCE EVALUATION OF CULTURAL ARTIFICIAL BEE COLONY AND CULTURAL ARTIFICIAL FISH SWARM ALGORITHM

2019 ◽  
Vol 6 (4) ◽  
pp. 43
Author(s):  
HADIR ADEBIYI BUSAYO ◽  
TIJANI SALAWUDEEN AHMED ◽  
FOLASHADE O. ADEBIYI RISIKAT ◽  
◽  
◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Artificial Bee Colony ◽  
Artificial Fish Swarm Algorithm ◽  
Bee Colony ◽  
Artificial Fish Swarm ◽  
Swarm Algorithm

Path Planning of Mobile Robot Using Improved Artificial Bee Colony Algorithm

2020 ◽  
Vol 38 (9A) ◽  
pp. 1384-1395
Author(s):  
Rakaa T. Kamil ◽  
Mohamed J. Mohamed ◽  
Bashra K. Oleiwi
Keyword(s):  
Mobile Robot ◽  
Comparative Research ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Dynamic Control ◽  
Computational Time ◽  
Bee Colony ◽  
Shortest Distance ◽  
Minimum Number ◽  
Cubic Polynomial

A modified version of the artificial Bee Colony Algorithm (ABC) was suggested namely Adaptive Dimension Limit- Artificial Bee Colony Algorithm (ADL-ABC). To determine the optimum global path for mobile robot that satisfies the chosen criteria for shortest distance and collision–free with circular shaped static obstacles on robot environment. The cubic polynomial connects the start point to the end point through three via points used, so the generated paths are smooth and achievable by the robot. Two case studies (or scenarios) are presented in this task and comparative research (or study) is adopted between two algorithm’s results in order to evaluate the performance of the suggested algorithm. The results of the simulation showed that modified parameter (dynamic control limit) is avoiding static number of limit which excludes unnecessary Iteration, so it can find solution with minimum number of iterations and less computational time. From tables of result if there is an equal distance along the path such as in case A (14.490, 14.459) unit, there will be a reduction in time approximately to halve at percentage 5%.

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