Mine blast harmony search: A new hybrid optimization method for improving exploration and exploitation capabilities

Ali Sadollah, Hassan Sayyaadi, Do Guen Yoo, Ho Min Lee, Joong Hoon Kim

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

This paper proposes a hybrid optimization method that combines the power of the harmony search (HS) with the mine blast algorithm (MBA). The resulting mine blast harmony search (MBHS) uses MBA for exploration and HS for exploitation. The HS is inspired by the improvisation process of musicians, while the MBA is derived based on explosion of landmines. The HS used in the hybrid algorithm is an improved version, introducing a new concept for the harmony memory size, while the MBA is modified in terms of its mathematical formulation. Several numerical problems and benchmarks with many design variables and constraints are used to validate MBHS, and the optimization results are compared with those from various algorithms in the literature. The numerical results show that the proposed hybrid method provides better exploitation ability (especially in the final iterations) and enjoys mature convergence to the optimum solution.

Original languageEnglish
Pages (from-to)548-564
Number of pages17
JournalApplied Soft Computing Journal
Volume68
DOIs
Publication statusPublished - 2018 Jul 1

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Keywords

  • Global optimization
  • Harmony search
  • Hybrid metaheuristic methods
  • Large-scale problems
  • Mine blast algorithm

ASJC Scopus subject areas

  • Software

Cite this

Mine blast harmony search : A new hybrid optimization method for improving exploration and exploitation capabilities. / Sadollah, Ali; Sayyaadi, Hassan; Yoo, Do Guen; Lee, Ho Min; Kim, Joong Hoon.

In: Applied Soft Computing Journal, Vol. 68, 01.07.2018, p. 548-564.

Research output: Contribution to journalArticle

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