scholarly journals A Metaheuristic Algorithm for VLSI Floorplanning Problem

2019 ◽  
Vol 8 (2S5) ◽  
pp. 249-254
Keyword(s):  
Genetic Algorithm ◽  
Large Scale ◽  
Search Algorithm ◽  
Design Method ◽  
Harmony Search ◽  
Optimal Solution ◽  
Harmony Search Algorithm ◽  
Chip Area ◽  
Optimum Solution ◽  
Vlsi Floorplanning

Floorplanning plays an important role within the physical design method of very large Scale Integrated (VLSI) chips. It’s a necessary design step to estimate the chip area before the optimized placement of digital blocks and their interconnections. Since VLSI floorplanning is an NP-hard problem, several improvement techniques were adopted to find optimal solution. In this paper, a hybrid algorithm which is genetic algorithm combined with music-inspired Harmony Search (HS) algorithm is employed for the fixed die outline constrained floorplanning, with the ultimate aim of reducing the full chip area. Initially, B*-tree is employed to come up with the first floorplan for the given rectangular hard modules and so Harmony Search algorithm is applied in any stages in genetic algorithm to get an optimum solution for the economical floorplan. The experimental results of the HGA algorithm are obtained for the MCNC benchmark circuits

Portfolio optimization using genetic algorithm and harmony search algorithm with varying operators and parameter values

2019 ◽  
Author(s):  
Kee Huong Lai ◽  
Woon Jeng Siow ◽  
Ahmad Aniq bin Mohd Nooramin Kaw ◽  
Pauline Ong ◽  
Zarita Zainuddin
Keyword(s):  
Genetic Algorithm ◽  
Portfolio Optimization ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Parameter Values

scholarly journals Hybrid Multilevel Thresholding and Improved Harmony Search Algorithm for Segmentation

2018 ◽  
Vol 8 (6) ◽  
pp. 4593 ◽  
Author(s):  
Erwin Erwin ◽  
Saparudin Saparudin ◽  
Wulandari Saputri
Keyword(s):  
High Performance ◽  
Search Algorithm ◽  
Signal To Noise Ratio ◽  
Harmony Search ◽  
Optimal Solution ◽  
Harmony Search Algorithm ◽  
Multilevel Thresholding ◽  
Improved Harmony Search ◽  
High Degree ◽  
Improved Harmony Search Algorithm

This paper proposes a new method for image segmentation is hybrid multilevel thresholding and improved harmony search algorithm. Improved harmony search algorithm which is a method for finding vector solutions by increasing its accuracy. The proposed method looks for a random candidate solution, then its quality is evaluated through the Otsu objective function. Furthermore, the operator continues to evolve the solution candidate circuit until the optimal solution is found. The dataset used in this study is the retina dataset, tongue, lenna, baboon, and cameraman. The experimental results show that this method produces the high performance as seen from peak signal-to-noise ratio analysis (PNSR). The PNSR result for retinal image averaged 40.342 dB while for the average tongue image 35.340 dB. For lenna, baboon and cameramen produce an average of 33.781 dB, 33.499 dB, and 34.869 dB. Furthermore, the process of object recognition and identification is expected to use this method to produce a high degree of accuracy.

Hybrid Data Mining Approach for Image Segmentation Based Classification

Biometrics ◽  
2017 ◽  
pp. 1543-1561 ◽  
Author(s):  
Mrutyunjaya Panda ◽  
Aboul Ella Hassanien ◽  
Ajith Abraham
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Image Segmentation ◽  
Search Algorithm ◽  
Rbf Neural Network ◽  
Harmony Search ◽  
Optimal Solution ◽  
Solution Space ◽  
Harmony Search Algorithm ◽  
Data Mining Technique

Evolutionary harmony search algorithm is used for its capability in finding solution space both locally and globally. In contrast, Wavelet based feature selection, for its ability to provide localized frequency information about a function of a signal, makes it a promising one for efficient classification. Research in this direction states that wavelet based neural network may be trapped to fall in a local minima whereas fuzzy harmony search based algorithm effectively addresses that problem and able to get a near optimal solution. In this, a hybrid wavelet based radial basis function (RBF) neural network (WRBF) and feature subset harmony search based fuzzy discernibility classifier (HSFD) approaches are proposed as a data mining technique for image segmentation based classification. In this paper, the authors use Lena RGB image; Magnetic resonance image (MR) and Computed Tomography (CT) Image for analysis. It is observed from the obtained simulation results that Wavelet based RBF neural network outperforms the harmony search based fuzzy discernibility classifiers.

scholarly journals VIBRANT SEARCH MECHANISM FOR NUMERICAL OPTIMIZATION FUNCTIONS

2018 ◽  
Author(s):  
Moh’d Khaled Yousef Shambour
Keyword(s):  
Convergence Rates ◽  
Search Algorithm ◽  
Harmony Search ◽  
Optimal Solution ◽  
Search Space ◽  
Harmony Search Algorithm ◽  
Search Performance ◽  
Search Spaces ◽  
Search Mechanism ◽  
Heuristic Technique

Recently, various variants of evolutionary algorithms have been offered to optimize the exploration and exploitation abilities of the search mechanism. Some of these variants still suffer from slow convergence rates around the optimal solution. In this paper, a novel heuristic technique is introduced to enhance the search capabilities of an algorithm, focusing on certain search spaces during evolution process. Then, employing a heuristic search mechanism that scans an entire space before determining the desired segment of that search space. The proposed method randomly updates the desired segment by monitoring the algorithm search performance levels on different search space divisions. The effectiveness of the proposed technique is assessed through harmony search algorithm (HSA). The performance of this mechanism is examined with several types of benchmark optimization functions, and the results are compared with those of the classic version and two variants of HSA. The experimental results demonstrate that the proposed technique achieves the lowest values (best results) in 80% of the non-shifted functions, whereas only 33.3% of total experimental cases are achieved within the shifted functions in a total of 30 problem dimensions. In 100 problem dimensions, 100% and 25% of the best results are reported for non-shifted and shifted functions, respectively. The results reveal that the proposed technique is able to orient the search mechanism toward desired segments of search space, which therefore significantly improves the overall search performance of HSA, especially for non-shifted optimization functions.   

Optimal Network Reconfiguration of Large-Scale Distribution System Using Harmony Search Algorithm

2011 ◽  
Vol 26 (3) ◽  
pp. 1080-1088 ◽  
Author(s):  
Rayapudi Srinivasa Rao ◽  
Sadhu Venkata Lakshmi Narasimham ◽  
Manyala Ramalinga Raju ◽  
A. Srinivasa Rao
Keyword(s):  
Distribution System ◽  
Large Scale ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Network Reconfiguration ◽  
Optimal Network

An alternative approach to a harmony search algorithm for a construction site layout problem

2010 ◽  
Vol 37 (12) ◽  
pp. 1560-1571 ◽  
Author(s):  
Roozbeh Gholizadeh ◽  
Gholamrez Ghodrati Amiri ◽  
Benyamin Mohebi
Keyword(s):  
Search Algorithm ◽  
Harmony Search ◽  
Great Influence ◽  
Original Method ◽  
Harmony Search Algorithm ◽  
Construction Site ◽  
Alternative Approach ◽  
Optimum Solution ◽  
The Cost ◽  
Construction Site Layout

The task of positioning temporary facilities on a construction site has long been recognized as a factor of great influence on the cost of projects. This paper proposes the use of a recently developed harmony search (HS) algorithm to solve the problem of assigning a set of predetermined facilities to a set of preallocated locations within a construction site. Experiments with different parameter settings were conducted, and an alternative approach was used with a modified HS algorithm to overcome shortcomings of the original method. The proposed algorithm shows a rapid convergence to an optimum solution during the early stages of algorithm progress. In addition, comparisons with different variations of the HS algorithm and genetic algorithm (GA) are presented to demonstrate the efficiency of the proposed method and HS methodology in solving facility layout problems.

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