Recent Advances in Harmony Search

Geem, Zong Woo; Fesanghary, M.; Choi, Jeongyoon; Saka, M.P.; Williams, J.; Ayvaz, M. Tamer; Ryu, Sam

doi:10.5772/6135

Cited by 7 publications

(1 citation statement)

References 29 publications

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“…. , 𝑗) would be arbitrarily chosen out of a group of all candidate values {𝑥𝑖(1), 𝑥𝑖(2), … , 𝑥𝑖(𝑘𝑖)} with a probability of PRandom (random consideration); or it would be chosen out of a group of values kept in the HM with a probability of PMemory (memory consideration); or with a little change by moving to neighbor values 𝑥𝑖(𝑘 ± 𝑚), with a probability of PPitch (pitch adjustment) [13].…”

Section: Step 3: Improvise a New Harmony (Solution)mentioning

confidence: 99%

Review on the parameter settings in harmony search algorithm applied to combinatorial optimization problems

Ahmed

Hamdan

Muhammed

et al. 2022

IJEECS

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Harmony search algorithm (HSA) is relatively considered as one of the most recent metaheuristic algorithms. HSA is a modern - nature algorithm that simulates the musicians’ natural process of musical improvisation to enhance their instrument’s note to find a state of pleasant (harmony) according to aesthetic standards. Lots of variants of HSA have been suggested to tackle combinatorial optimization problems. They range from hybridizing some components of other metaheuristic approaches (to improve the HSA) to taking some concepts of HSA and utilizing them to improve other metaheuristic methods. This stud y reviews research pertaining to parameter settings of HSA and its applications to efficiently solve hard combinatorial optimization problems.

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Section: Step 3: Improvise a New Harmony (Solution)mentioning

confidence: 99%