Self-adaptive multi-objective harmony search for optimal design of water distribution networks

Young Hwan Choi, Ho Min Lee, Do Guen Yoo, Joong Hoon Kim

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)


In multi-objective optimization computing, it is important to assign suitable parameters to each optimization problem to obtain better solutions. In this study, a self-adaptive multi-objective harmony search (SaMOHS) algorithm is developed to apply the parameter-setting-free technique, which is an example of a self-adaptive methodology. The SaMOHS algorithm attempts to remove some of the inconvenience from parameter setting and selects the most adaptive parameters during the iterative solution search process. To verify the proposed algorithm, an optimal least cost water distribution network design problem is applied to three different target networks. The results are compared with other well-known algorithms such as multi-objective harmony search and the non-dominated sorting genetic algorithm-II. The efficiency of the proposed algorithm is quantified by suitable performance indices. The results indicate that SaMOHS can be efficiently applied to the search for Pareto-optimal solutions in a multi-objective solution space.

Original languageEnglish
Pages (from-to)1-21
Number of pages21
JournalEngineering Optimization
Publication statusAccepted/In press - 2017 Jan 21


  • multi-objective harmony search
  • Optimal design of water distribution network
  • parameter-setting-free
  • self-adaptive

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Optimization
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Applied Mathematics


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