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A Population-Based Strategic Oscillation Algorithm for Linear Ordering Problem with Cumulative Costs

  • Conference paper
Evolutionary Computation in Combinatorial Optimization (EvoCOP 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7832))

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Abstract

This paper presents a Population-based Strategic Oscillation (denoted by PBSO) algorithm for solving the linear ordering problem with cumulative costs (denoted by LOPCC). The proposed algorithm integrates several distinguished features, such as an adaptive strategic oscillation local search procedure and an effective population updating strategy. The proposed PBSO algorithm is compared with several state-of-the-art algorithms on a set of public instances up to 100 vertices, showing its efficacy in terms of both solution quality and efficiency. Moreover, several important ingredients of the PBSO algorithm are analyzed.

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Author information

Authors and Affiliations

  1. Systems Engineering Research Institute, Beijing, 100094, China

    Wei Xiao, Guang Liu & Shanshan Cui

  2. SMART, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China

    Wenqing Chu, Zhipeng Lü & Tao Ye

Authors
  1. Wei Xiao
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  2. Wenqing Chu
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  3. Zhipeng Lü
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  4. Tao Ye
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  5. Guang Liu
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  6. Shanshan Cui
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Leipzig, Johannisgasse 26, 04103, Leipzig, Germany

    Martin Middendorf

  2. IKERBASQUE, Basque Foundation for Science, Department of Computer Science and Artificial Intelligence, University of the Basque Country, Paseo Manuel Lardizabal 1, 20018, Donostia, Spain

    Christian Blum

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© 2013 Springer-Verlag Berlin Heidelberg

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Xiao, W., Chu, W., Lü, Z., Ye, T., Liu, G., Cui, S. (2013). A Population-Based Strategic Oscillation Algorithm for Linear Ordering Problem with Cumulative Costs. In: Middendorf, M., Blum, C. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2013. Lecture Notes in Computer Science, vol 7832. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37198-1_5

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  • DOI: https://doi.org/10.1007/978-3-642-37198-1_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37197-4

  • Online ISBN: 978-3-642-37198-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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