A population-based strategic oscillation algorithm for linear ordering problem with cumulative costs

  • Authors:
  • Wei Xiao;Wenqing Chu;Zhipeng Lü;Tao Ye;Guang Liu;Shanshan Cui

  • Affiliations:
  • Systems Engineering Research Institute, Beijing, China;SMART, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China;SMART, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China;SMART, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China;Systems Engineering Research Institute, Beijing, China;Systems Engineering Research Institute, Beijing, China

  • Venue:
  • EvoCOP'13 Proceedings of the 13th European conference on Evolutionary Computation in Combinatorial Optimization
  • Year:
  • 2013

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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.