A Cooperative Coevolution Hyper-Heuristic Framework for Workflow Scheduling Problem

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Xiao:ieeeServiceC,

• author = "Qin-zhe Xiao and Jinghui Zhong and Liang Feng and Linbo Luo and Jianming Lv",
• title = "A Cooperative Coevolution Hyper-Heuristic Framework for Workflow Scheduling Problem",
• journal = "IEEE Transactions on Services Computing",
• year = "2022",
• volume = "15",
• number = "1",
• pages = "150--163",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/TSC.2019.2923912",
• ISSN = "1939-1374",
• abstract = "Workflow scheduling problem (WSP) is a well-known combinatorial optimization problem, which is defined to assign a series of interconnected tasks to the available resources to meet user defined Quality of Service (QoS). Traditional guided random search methods and heuristic based methods are either require expensive computational cost or heavily rely on human's empirical knowledge, which makes them inconvenient for practical applications. To address the above issues, this paper proposes a cooperative coevolution hyper-heuristic framework to solve WSP with an objective of minimizing the completed time of workflow. In particular, in the proposed framework, two hyper-heuristics, namely, the task selection rule (TSR) and the resource selection rule (RSR), are learned automatically by a cooperative coevolution genetic programming algorithm. The TSR is used to select a ready task for scheduling, while the RSR is used to allocate resources to perform the selected task.To validate the effectiveness of the proposed framework, randomly generated workflow instances and four real-world workflows are used as test cases. Compared with several state-of-the-art methods, the hyper-heuristics found by our proposed framework demonstrate superior performance on all the test cases in terms of metrics including the schedule length ratio, speedup and efficiency",
• notes = "Also known as \cite{8744408}",

}

Genetic Programming entries for Qin-zhe Xiao Jinghui Zhong Liang Feng Linbo Luo Jianming Lv

Citations