Generating a Adhesive Nozzle Path by the Parameter-Setting-Free Harmony Search Algorithm for a Shoe-Upper Assembly Process

2018 ◽  
Vol 28 (1) ◽  
pp. 49-56
Author(s):  
Woo-Young Lee ◽  
Sung-Won Lee ◽  
Seung-Min Park ◽  
Tae-Hyoung Kim ◽  
Zong-Woo Geem ◽  
...  
2020 ◽  
Vol 10 (7) ◽  
pp. 2586
Author(s):  
Yong-Woon Jeong ◽  
Seung-Min Park ◽  
Zong Woo Geem ◽  
Kwee-Bo Sim

In this paper, we propose an advanced parameter-setting-free (PSF) scheme to solve the problem of setting the parameters for the harmony search (HS) algorithm. The use of the advanced PSF method solves the problems of the conventional PSF scheme that results from a large number of iterations and shows good results compared to fixing the parameters required for the HS algorithm. In addition, unlike the conventional PSF method, the advanced PSF method does not use additional memory. We expect the advanced PSF method to be applicable to various fields that use the HS algorithm because it reduces the memory utilization for operations while obtaining better results than conventional PSF schemes.


2014 ◽  
Vol 596 ◽  
pp. 192-195
Author(s):  
Ping Zhang ◽  
Peng Sun ◽  
Yi Ning Zhang ◽  
Guo Jun Li

Recently, a new meta-heuristic optimization algorithm–harmony search (HS) was developed, which imitates the behaviors of music improvisation. Although several variants and an increasing number of applications have appeared, one of its main difficulties is how to select suitable parameter values. In this paper, a self-adaptive harmony search algorithm (SaHS) proposed. In this algorithm, we design a new parameter setting strategy to directly tune the parameters in the search process, and balance the process of exploitation and exploration. Finally, we use SaHS to solve unconstrained optimization problems so as to profoundly study and analyze the performance of the SaHS. The results show that the SaHS has better convergence accuracy than the other three harmony search algorithms.


2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Zong Woo Geem

Economic dispatch is one of the popular energy system optimization problems. Recently, it has been solved by various phenomenon-mimicking metaheuristic algorithms such as genetic algorithm, tabu search, evolutionary programming, particle swarm optimization, harmony search, honey bee mating optimization, and firefly algorithm. However, those phenomenon-mimicking problems require a tedious and troublesome process of algorithm parameter value setting. Without a proper parameter setting, good results cannot be guaranteed. Thus, this study adopts a newly developed parameter-setting-free technique combined with the harmony search algorithm and applies it to the economic dispatch problem for the first time, obtaining good results. Hopefully more researchers in energy system fields will adopt this user-friendly technique in their own problems in the future.


2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
Kaiping Luo

The harmony search algorithm is a music-inspired optimization technology and has been successfully applied to diverse scientific and engineering problems. However, like other metaheuristic algorithms, it still faces two difficulties: parameter setting and finding the optimal balance between diversity and intensity in searching. This paper proposes a novel, self-adaptive search mechanism for optimization problems with continuous variables. This new variant can automatically configure the evolutionary parameters in accordance with problem characteristics, such as the scale and the boundaries, and dynamically select evolutionary strategies in accordance with its search performance. The new variant simplifies the parameter setting and efficiently solves all types of optimization problems with continuous variables. Statistical test results show that this variant is considerably robust and outperforms the original harmony search (HS), improved harmony search (IHS), and other self-adaptive variants for large-scale optimization problems and constrained problems.


2013 ◽  
Vol 32 (9) ◽  
pp. 2412-2417
Author(s):  
Yue-hong LI ◽  
Pin WAN ◽  
Yong-hua WANG ◽  
Jian YANG ◽  
Qin DENG

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