An enhanced harmony search (ENHS) algorithm for solving optimization problems

Taj, T. A.; Khan, Talha Ahmed; Ijaz, Imran

doi:10.1109/elconrusnw.2014.6839208

Cited by 5 publications

(2 citation statements)

References 19 publications

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“…BW k = (BW max − BW min )e −k + BW min (18) where HMCR max and HMCR min are the maximum and minimum values of harmony memory considering rate, respectively; k is the current iteration number; i tmax is the maximum number of iterations; PAR max and PAR min are the maximum and minimum values of the pitch-adjusting rate, respectively; BW max and BW min are the maximum and minimum values of bandwidth, respectively.…”

Section: Step3: Generation Of Non-dominated Solutionsmentioning

confidence: 99%

“…Harmony Search (HS) is a global heuristic search algorithm proposed by Geem Korean in 2001 [16]. This algorithm emulates the process of a music player adjusting various instrument pitches to reach the most pleasant harmonies status [17], [18]. The HS algorithm features several advantages including simple structure, requirement of few parameters, rapid convergence and robustness, [19].…”

Section: Introductionmentioning

confidence: 99%

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Optimum Location and Parameter Setting of STATCOM Based on Improved Differential Evolution Harmony Search Algorithm

Zhang

et al. 2020

IEEE Access

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Identification of the optimum location and capacity of Static Synchronous Compensator (STAT-COM) in power grids has been given much attention to maximize its technical performance while minimizing operational cost. In this regard, a new multi-objective optimization model that minimizes power loss, enhances system stability and reduces operational cost of STATCOMs is presented in this paper. To overcome the issue of the harmony search (HS) optimization algorithm in solving high-dimensional multi-objective optimization problem, an improved differential evolution harmony search (DEHS) algorithm is proposed. In this algorithm, mutation and crossover operations are adopted instead of the original pitch adjustment operation adopted in the HS optimization algorithm, which enhances the algorithm global search ability. Moreover, opposition-based learning technique is incorporated to the process to broaden the diversity of variables and hence improving the search efficiency of the algorithm. The proposed algorithm is employed to identify the optimal allocation and sizing of multiple STATCOMs within the IEEE 30-bus system. Results reveal the superiority of the proposed optimization algorithm over the conventional multi-objectives adaptive harmony search algorithm. INDEX TERMS Flexible ac transmission systems, static synchronous compensator, system optimization, harmony search algorithm.

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Section: Step3: Generation Of Non-dominated Solutionsmentioning

confidence: 99%