Memetic Artificial Bee Colony for Integer Programming

2014 ◽  
pp. 268-277 ◽  
Author(s):  
Ahmed Fouad Ali ◽  
Aboul Ella Hassanien ◽  
Vaclav Snasel
Keyword(s):  
Integer Programming ◽  
Artificial Bee Colony ◽  
Bee Colony

scholarly journals A Shuffle-Based Artificial Bee Colony Algorithm for Solving Integer Programming and Minimax Problems

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1211
Author(s):  
Ivona Brajević
Keyword(s):  
Integer Programming ◽  
Artificial Bee Colony ◽  
Optimization Problems ◽  
Minimax Problems ◽  
Abc Algorithm ◽  
Bee Colony ◽  
Effective Performance ◽  
Complex Optimization ◽  
Overall Performance ◽  
Integer Programming Problems

The artificial bee colony (ABC) algorithm is a prominent swarm intelligence technique due to its simple structure and effective performance. However, the ABC algorithm has a slow convergence rate when it is used to solve complex optimization problems since its solution search equation is more of an exploration than exploitation operator. This paper presents an improved ABC algorithm for solving integer programming and minimax problems. The proposed approach employs a modified ABC search operator, which exploits the useful information of the current best solution in the onlooker phase with the intention of improving its exploitation tendency. Furthermore, the shuffle mutation operator is applied to the created solutions in both bee phases to help the search achieve a better balance between the global exploration and local exploitation abilities and to provide a valuable convergence speed. The experimental results, obtained by testing on seven integer programming problems and ten minimax problems, show that the overall performance of the proposed approach is superior to the ABC. Additionally, it obtains competitive results compared with other state-of-the-art algorithms.

Self-Adaptive and Adaptive Parameter Control in Improved Artificial Bee Colony Algorithm

Informatica ◽  
2017 ◽  
Vol 28 (3) ◽  
pp. 415-438 ◽  
Author(s):  
Bekir Afşar ◽  
Doğan Aydin ◽  
Aybars Uğur ◽  
Serdar Korukoğlu
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Parameter Control ◽  
Adaptive Parameter ◽  
Bee Colony ◽  
Adaptive Parameter Control ◽  
Self Adaptive

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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