A Comparative Study of Exploration Ability of Harmony Search Algorithms

2017 ◽  
pp. 22-31
Author(s):  
Anupam Yadav ◽  
Neha Yadav ◽  
Joong Hoon Kim
Keyword(s):  
Comparative Study ◽  
Harmony Search ◽  
Search Algorithms

A hybrid job scheduling algorithm based on Tabu and Harmony search algorithms

2019 ◽  
Vol 75 (12) ◽  
pp. 7994-8011 ◽  
Author(s):  
Hadeel Alazzam ◽  
Esraa Alhenawi ◽  
Rizik Al-Sayyed
Keyword(s):  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Harmony Search ◽  
Search Algorithms ◽  
Job Scheduling Algorithm

scholarly journals OPTIMASI PENJADWALAN PRODUKSI MENGGUNAKAN PENDEKATAN ALGORITMA HARMONY SEARCH DI PT ADI SATRIA ABADI (ASA

2020 ◽  
Vol 11 (1) ◽  
pp. 7-12
Author(s):  
Inaaratul Chusna Ichda Purwanto ◽  
Yohanes Anton Nugroho ◽  
Suseno Suseno
Keyword(s):  
Search Algorithm ◽  
Harmony Search ◽  
Search Algorithms ◽  
Harmony Search Algorithm ◽  
Due Date ◽  
Average Value ◽  
Scheduling Method ◽  
Time Savings ◽  
A Company ◽  
Selection Of

PT Adi Satria Abadi (ASA) is a company engaged in the processing of leather, especially sheep skin and goat skin, which is used for the manufacture of golf gloves. The problem faced by the company is the production process that exceeds the due date to other customers who order products at PT ASA. From the research, it is known that the cause is a company scheduling method that has not been organized so that the production sequence is concurrent. Selection of methods Harmony Search algorithms in scheduling are caused by delays. The Harmony Search algorithm can provide a better makespan value than the company method. The results of the company method obtain 0.9 months makespan average, the Harmony Search Algorithm method produces an average 0.8 months makespan. In addition, the use of the Harmony Search Algorithm method can reduce the average value of 0.1 months makespan. The results of the study in three months experienced time savings of 0.6 months, 0.6 months and 0.1 months respectively.

scholarly journals Segmentation of White Chali Arecanuts using Soft Computing Methods

2020 ◽  
Vol 9 (7) ◽  
pp. 1049-1055
Keyword(s):  
Differential Evolution ◽  
Harmony Search ◽  
Cuckoo Search ◽  
Search Algorithms ◽  
Fine Tuning ◽  
Experimental Result ◽  
Multilevel Thresholding ◽  
Low Contrast ◽  
Morphological Segmentation ◽  
Grading Systems

Performance of computer vision based grading systems is remarkably affected by the efficiency of object segmentation. The automatic segmentation of low contrast objects is a challenging task in various fruit and nut grading systems. In this paper background elimination of white chali arecanut images is carried out using morphological segmentation. The fine-tuning of edge threshold for morphological segmentation is achieved by obtaining threshold values from multilevel thresholding of original grayscale image. The best figure ground segmentation is selected by a network trained using shape parameters of the ground truth masks. The performance of morphological segmentation is evaluated for the best figure ground segmentations using precision, recall and F-scores. Comparison of segmentation performance is done by employing multilevel thresholding based on Otsu, Fuzzy c-mean, Harmony search, Differential Evolution and Cuckoo Search algorithms. The experimental result shows that, multilevel thresholding using Differential Evolution and Cuckoo Search algorithms yield best results for the fine-tuning of edge thresholds and hence the better segmentation performance of the white chali arecanuts

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