A new structural optimization method based on the harmony search algorithm

By Kang Seok Lee, Zong Woo Geem. 2004

1,225 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Civil and Structural Engineering, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/9230f69cfcf2b85b6035ab8fc9f0dbeea20c46a0

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In Artificial Intelligence

In Civil and Structural Engineering

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Citations in the corpus

Music-Inspired Harmony Search Algorithm (2009, methodology): “Many applications, excluding benchmark problems, have been summarised in [3].”
Harris hawks optimization: Algorithm and applications (2019, methodology): “The optimal results of HHO versus those attained by RANDOM [89], DAVID [89], SIMPLEX 389 [89], APPROX [89], GA1 [73], GA2 [63], HS [90], GSA [18], ESs [81], and CDE [91] are represented 390 in Table 13.”
An adaptive reanalysis method for genetic algorithm with application to fast truss optimization (2010, methodology): “a Presenta Saka [25]b Lee [24]b”
A Novel Order Reduction Method Using Cuckoo Search Algorithm (2015, methodology): “Harmony search algorithm inspired by musical improvisation [18], Big Bang Big Crunch (BB-BC) algorithm that relies on one of the evolution of the universe theories in physics and astronomy [19], and hybrid or advanced meta-heuristic search algorithms [20 22], etc.”
Shape optimization of structures for frequency constraints by sequential harmony search algorithm (2013, methodology): “The HS imitates the musical performance process which takes place when a musician searches for a better state of harmony (Lee and Geem 2004 ), and HS has been used by researchers for solving engineering optimization problems (Nahas and Thien-My 2010 , Jaberipour and Khorram 2011 , Karahan et al ”
Evolutionary level set method for structural topology optimization (2011, methodology): “Based on the thinking of a perfect state of harmony in musical processing, Lee and Geem [21] developed the implementation of harmony searching algorithm for structural optimization.”
Search group algorithm (2015, methodology): “For example, classical metaheuristic algorithms such as Simulated Annealing [5,6], Genetic Algorithms [7,8], Particle Swarm Optimization [6,9–11], Harmony Search [12–14] and Ant Colony Optimization [15], were employed.”