Journal of Heuristics

, Volume 25, Issue 4–5, pp 731–752 | Cite as

An effective multi-wave algorithm for solving the max-mean dispersion problem

  • Jiawei Song
  • Yang WangEmail author
  • Haibo Wang
  • Qinghua Wu
  • Abraham P. Punnen


We propose an effective multi-wave algorithm organized in multiple search phases for the max-mean dispersion problem, which offers enhancement of neighborhood search algorithms by incorporating the notion of persistent attractiveness in memory based strategies. In each wave, a vertical phase and a horizontal phase are first alternated to reach a boundary solution. Then a concluding horizontal phase is executed to search around this boundary solution for further solution refinement. Finally, an oscillation phase and a diversified initial solution generation phase focus on search diversification to build well-diversified initial solutions for subsequent waves and passes. Experimental results show that the proposed approach performs quite competitive with state-of-the-art algorithms in the literature. Additional analysis discloses the benefits of the key ingredients in the proposed algorithm.


Multi-wave algorithm Local search Adaptive memory Dispersion problems 



We are grateful to the reviewers whose comments have helped to improve our paper. This work was supported by the National Natural Science Foundation of China (Grant No. 71501157).


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Jiawei Song
    • 1
  • Yang Wang
    • 2
    Email author
  • Haibo Wang
    • 3
  • Qinghua Wu
    • 1
  • Abraham P. Punnen
    • 4
  1. 1.School of ManagementHuazhong University of Science and TechnologyWuhanChina
  2. 2.School of ManagementNorthwestern Polytechnical UniversityXi’anChina
  3. 3.Sanchez School of BusinessTexas A&M International UniversityLaredoUSA
  4. 4.Department of MathematicsSimon Fraser University SurreySurreyCanada

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