TY - JOUR
T1 - Harmony search algorithm for energy system applications
T2 - an updated review and analysis
AU - Nazari-Heris, Morteza
AU - Mohammadi-Ivatloo, Behnam
AU - Asadi, Somayeh
AU - Kim, Jin Hong
AU - Geem, Zong Woo
N1 - Publisher Copyright:
© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2019/9/3
Y1 - 2019/9/3
N2 - Recent advancements in energy systems have led to a series of new challenges in the decision-making process. Harmony search (HS) algorithm, which is a music-inspired optimisation technique, has been applied to some of these decision-making processes to obtain optimal set points within these energy systems. HS is based on the music improvisation process where musicians try to find better harmonies. Some of the advantages of HS method are that it is relatively simple to implement and require less algorithmic parameters. This paper aims to provide a comprehensive review on the applications of HS method to energy systems, that concentrate on two main objectives. First, the improved versions of HS introduced in recent studies will be reported. Second, contributed researches in energy systems by using HS will be analysed.
AB - Recent advancements in energy systems have led to a series of new challenges in the decision-making process. Harmony search (HS) algorithm, which is a music-inspired optimisation technique, has been applied to some of these decision-making processes to obtain optimal set points within these energy systems. HS is based on the music improvisation process where musicians try to find better harmonies. Some of the advantages of HS method are that it is relatively simple to implement and require less algorithmic parameters. This paper aims to provide a comprehensive review on the applications of HS method to energy systems, that concentrate on two main objectives. First, the improved versions of HS introduced in recent studies will be reported. Second, contributed researches in energy systems by using HS will be analysed.
UR - https://www.scopus.com/pages/publications/85059449863
UR - https://www.scopus.com/pages/publications/85059449863#tab=citedBy
U2 - 10.1080/0952813X.2018.1550814
DO - 10.1080/0952813X.2018.1550814
M3 - Article
AN - SCOPUS:85059449863
SN - 0952-813X
VL - 31
SP - 723
EP - 749
JO - Journal of Experimental and Theoretical Artificial Intelligence
JF - Journal of Experimental and Theoretical Artificial Intelligence
IS - 5
ER -