Enhanced Bee Colony Algorithm for Solving Travelling Salesperson Problem

Author(s):  
Prateek Agrawal
2019 ◽  
Vol 2 (3) ◽  
pp. 508-517
Author(s):  
FerdaNur Arıcı ◽  
Ersin Kaya

Optimization is a process to search the most suitable solution for a problem within an acceptable time interval. The algorithms that solve the optimization problems are called as optimization algorithms. In the literature, there are many optimization algorithms with different characteristics. The optimization algorithms can exhibit different behaviors depending on the size, characteristics and complexity of the optimization problem. In this study, six well-known population based optimization algorithms (artificial algae algorithm - AAA, artificial bee colony algorithm - ABC, differential evolution algorithm - DE, genetic algorithm - GA, gravitational search algorithm - GSA and particle swarm optimization - PSO) were used. These six algorithms were performed on the CEC’17 test functions. According to the experimental results, the algorithms were compared and performances of the algorithms were evaluated.


Author(s):  
Ramandeep Kaur

A lot of research has been done in the field of cloud computing in computing domain.  For its effective performance, variety of algorithms has been proposed. The role of virtualization is significant and its performance is dependent on VM Migration and allocation. More of the energy is absorbed in cloud; therefore, the utilization of numerous algorithms is required for saving energy and efficiency enhancement in the proposed work. In the proposed work, green algorithm has been considered with meta heuristic algorithms, ABC (Artificial Bee colony .Every server has to perform different or same functions. A cloud computing infrastructure can be modelled as Primary Machineas a set of physical Servers/host PM1, PM2, PM3… PMn. The resources of cloud infrastructure can be used by the virtualization technology, which allows one to create several VMs on a physical server or host and therefore, lessens the hardware amount and enhances the resource utilization. The computing resource/node in cloud is used through the virtual machine. To address this problem, data centre resources have to be managed in resource -effective manner for driving Green Cloud computing that has been proposed in this work using Virtual machine concept with ABC and Neural Network optimization algorithm. The simulations have been carried out in CLOUDSIM environment and the parameters like SLA violations, Energy consumption and VM migrations along with their comparison with existing techniques will be performed.


2019 ◽  
Vol 6 (4) ◽  
pp. 43
Author(s):  
HADIR ADEBIYI BUSAYO ◽  
TIJANI SALAWUDEEN AHMED ◽  
FOLASHADE O. ADEBIYI RISIKAT ◽  
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2020 ◽  
Vol 38 (9A) ◽  
pp. 1384-1395
Author(s):  
Rakaa T. Kamil ◽  
Mohamed J. Mohamed ◽  
Bashra K. Oleiwi

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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