A hybrid multi-objective artificial bee colony algorithm for flexible task scheduling problems in cloud computing system
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A hybrid multi-objective artificial bee colony algorithm for flexible task scheduling problems in cloud computing system Jun-qing Li1,2
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Yun-qi Han2
Received: 4 April 2018 / Revised: 3 July 2019 / Accepted: 25 November 2019 Springer Science+Business Media, LLC, part of Springer Nature 2019
Abstract In this study, the flexible task scheduling problem in a cloud computing system is studied and solved by a hybrid discrete artificial bee colony (ABC) algorithm, where the considered problem is firstly modeled as a hybrid flowshop scheduling (HFS) problem. Both a single objective and multiple objectives are considered. In multiple objective HFS problems, three objectives, i.e., minimization of the maximum completion time, maximum device workload, and total workloads of all devices, are considered simultaneously. Two different kinds of HFS are considered, i.e., HFS with identical parallel machines and HFS with unrelated machines. In the proposed algorithm, three types of artificial bees are included as in the classical ABC algorithm, i.e., the employed bee, the onlooker bee, and the scout bee. Each solution is represented as an integer string. To consider the problem features, several different types of perturbation structures are investigated to enhance the searching abilities. An improved version of the adaptive perturbation structure is embedded in the proposed algorithm to balance the exploitation and exploration ability. A simple but efficient selection and updated approach are applied to enhance the exploitation process. To further improve the exploitation abilities, a deep-exploitation operator is designed. An improved scout bee employed with different local search methods for the best food source or the abandoned solution is designed and can increase the convergence ability of the proposed algorithm. The proposed algorithm is tested on sets of the well-known benchmark instances, and the performance of the proposed algorithm is verified. Keywords Hybrid flowshop scheduling problem Artificial bee colony algorithm Cloud system Flexible task scheduling
1 Introduction With the development and applications of the cloud system, the task scheduling problem in the cloud computing system has gained increasingly more research focuses during recent years [1–3]. In the cloud system, the jobs proposed by the users should be assigned to capable devices, and generally, each job contains several consecutive tasks that should be processed in a certain sequence on different or same devices. The whole procedure can be modeled as a hybrid flowshop scheduling (HFS) problem & Jun-qing Li [email protected] 1
School of Computer Science, Liaocheng University, Liaocheng 252059, People’s Republic of China
2
School of Information Science and Engineering, Shandong Normal University, Jinan 250014, People’s Republic of China
[4]. The task scheduling in the cloud system has been studied during recent years, such as Wang et al. developed multidisciplinary approaches to artificial swa
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