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

ABSTRACT

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.

KEYWORDS:

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

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Joong Hoon Kim http://orcid.org/0000-0002-3729-7560

Additional information

Funding

This work was supported by a grant from the National Research Foundation (NRF) of Korea, funded by the Korean Government (MSIP) [grant number NRF-2016R1A2A1A05005306].