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Brain Storm Optimization Algorithms pp 35–59Cite as

Brain Storm Optimization for Test Task Scheduling Problem

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Part of the book series: Adaptation, Learning, and Optimization ((ALO,volume 23))

Abstract

The test task scheduling problem (TTSP) has attracted increasing attention due to the wide range of automatic test systems applications. It is one kind of combinatorial optimization problem with the property of multimodal. There are a lot of global optima and local optima in its huge solution space. Brain storm optimization algorithm (BSO) is a newly proposed swarm intelligence algorithm, which can utilize the evolutionary information of solution space. BSO has two main operations including convergent operation and divergent operation to balance the exploration and exploitation ability in the search process. In addition, the clustering strategy in BSO can explore different regions simultaneously regarding the multimodal property. The generation of new solutions depends on several ways, which greatly improve the possibility of finding better solutions. According to the characteristic of TTSP, BSO is more suitable for solving TTSP comparing to other metaheuristic algorithms. In this chapter, BSO is first applied to solving TTSP cooperating with a real number coding strategy. For single-objective TTSP, BSO divides the solution space into several clusters and produces the new solution based on various methods. Moreover, some modifications are proposed on BSO for solving multi-objective TTSP. It mainly includes the determination of centers and the reservation of better solutions. From the point of view of single objective and multi-objective problem, BSO has better performance comparing to recent scheduling algorithms for solving TTSP.

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Acknowledgements

This research is supported by the National Natural Science Foundation of China under Grant No. 61671041, 61101153, 61806119, 61773119, 61703256, and 61771297; in part by the Shenzhen Science and Technology Innovation Committee under grant number ZDSYS201703031748284; and in part by the Fundamental Research Funds for the Central Universities under Grant GK201703062.

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Authors and Affiliations

  1. School of Electronic and Information Engineering, Beihang University, Beijing, 100191, China

    Hui Lu & Rongrong Zhou

  2. School of Computer Science, Shaanxi Normal University, Xi’an, 710119, China

    Shi Cheng

  3. Shenzhen Key Lab of Computational Intelligence, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China

    Yuhui Shi

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  1. Hui Lu
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Correspondence to Hui Lu .

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Editors and Affiliations

  1. School of Computer Science, Shaanxi Normal University, Xi’an, China

    Shi Cheng

  2. Shenzhen Key Laboratory of Computational Intelligence, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

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Lu, H., Zhou, R., Cheng, S., Shi, Y. (2019). Brain Storm Optimization for Test Task Scheduling Problem. In: Cheng, S., Shi, Y. (eds) Brain Storm Optimization Algorithms. Adaptation, Learning, and Optimization, vol 23. Springer, Cham. https://doi.org/10.1007/978-3-030-15070-9_2

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