A New Optimization on Harmony Search Algorithm for Exam Timetabling System

2020 ◽  
Vol 19 (01) ◽  
pp. 2040009 ◽  
Author(s):  
Khaled Alomari ◽  
Osama Almarashdi ◽  
Ala Marashdh ◽  
Belal Zaqaibeh
Keyword(s):  
Search Algorithm ◽  
Harmony Search ◽  
Three Dimensional ◽  
Optimal Solution ◽  
Triangular Matrix ◽  
Harmony Search Algorithm ◽  
Huge Number ◽  
Exam Timetabling ◽  
General Constraints ◽  
Upper Triangular Matrix

Preparing an optimal exam timetable in universities is challenging for head of departments, especially for colleges with multiple number of departments, courses, and students. Harmony search algorithm is used by many researchers to solve this problem but none of them could get an optimal solution. In this paper, a new algorithm which is called optimised harmony search algorithm with distributed selections is proposed by optimising the harmony search algorithm and the genetic algorithm. The new algorithm could satisfy hard, soft, and general constraints and generate an optimal exam timetable for a huge number of courses and students. The proposed algorithm is implemented and applied on Jadara University, the algorithm uses an upper triangular matrix to reduce relationships and memory usage, a three-dimensional matrix to ease the exams timetable management a deterministic number generators to eliminate timeslots conflicts, and backtracking algorithm to enhance the population selections. Lecturers and students’ feedback showed a good satisfaction as well the system results.

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.   

scholarly journals An Elite Decision Making Harmony Search Algorithm for Optimization Problem

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Lipu Zhang ◽  
Yinghong Xu ◽  
Yousong Liu
Keyword(s):  
Decision Making ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Optimal Solution ◽  
Harmony Search Algorithm ◽  
Solution Vector ◽  
Integer Variables ◽  
Design Variables ◽  
New Variant

This paper describes a new variant of harmony search algorithm which is inspired by a well-known item “elite decision making.” In the new algorithm, the good information captured in the current global best and the second best solutions can be well utilized to generate new solutions, following some probability rule. The generated new solution vector replaces the worst solution in the solution set, only if its fitness is better than that of the worst solution. The generating and updating steps and repeated until the near-optimal solution vector is obtained. Extensive computational comparisons are carried out by employing various standard benchmark optimization problems, including continuous design variables and integer variables minimization problems from the literature. The computational results show that the proposed new algorithm is competitive in finding solutions with the state-of-the-art harmony search variants.

An Improved Harmony Search Algorithm with Application

2014 ◽  
Vol 687-691 ◽  
pp. 1367-1372
Author(s):  
Jian Ping Li ◽  
Ai Ping Lu ◽  
Hao Chang Wang ◽  
Xin Li ◽  
Pan Chi Li
Keyword(s):  
Population Size ◽  
Search Algorithm ◽  
Harmony Search ◽  
Optimal Solution ◽  
Harmony Search Algorithm ◽  
Global Optimal Solution ◽  
Improved Harmony Search ◽  
Global Optimal ◽  
Improved Harmony Search Algorithm ◽  
Harmony Memory

In classical harmony search algorithm, only one harmony vector is obtained in each of iteration, which affects its search ability. We propose an improve harmony search algorithm in this paper. In our approach, the number of harmony vectors obtained in each of iteration is equivalent to the population size, and all newly generated harmony vectors are put into the harmony memory array. Then, all harmony vectors are sorted by descending order of the fitness, and the first half individuals are served as the next generation of populations. Experimental results show that our approach is obviously superior to the classical one under the same iteration steps and the same running time, which reveals that our approach can effectively generate the excellent individuals approximating the global optimal solution and enhance the optimization ability of classical harmony search algorithm.

Harmony Search Algorithm

2018 ◽  
pp. 1-30 ◽  
Author(s):  
Alireza Askarzadeh ◽  
Esmat Rashedi
Keyword(s):  
Optimization Problems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Optimal Solution ◽  
Harmony Search Algorithm ◽  
Computational Time ◽  
Engineering Applications ◽  
Heuristic Search Algorithm ◽  
And Performance ◽  
Significant Attention

Harmony search (HS) is a meta-heuristic search algorithm which tries to mimic the improvisation process of musicians in finding a pleasing harmony. In recent years, due to some advantages, HS has received a significant attention. HS is easy to implement, converges quickly to the optimal solution and finds a good enough solution in a reasonable amount of computational time. The merits of HS algorithm have led to its application to optimization problems of different engineering areas. In this chapter, the concepts and performance of HS algorithm are shown and some engineering applications are reviewed. It is observed that HS has shown promising performance in solving difficult optimization problems and different versions of this algorithm have been developed. In the next years, it is expected that HS is applied to more real optimization problems.

scholarly journals Harmony Search Optimization of Nozzle Movement for Additive Manufacturing of Concrete Structures and Concrete Elements

2020 ◽  
Vol 10 (12) ◽  
pp. 4413 ◽  
Author(s):  
Yusuf Toklu ◽  
Gebrail Bekdaş ◽  
Zong Geem
Keyword(s):  
Additive Manufacturing ◽  
Search Algorithm ◽  
Harmony Search ◽  
Three Dimensional ◽  
Harmony Search Algorithm ◽  
Three Dimensional Printing ◽  
Search Optimization ◽  
Concrete Elements ◽  
Dimensional Printing ◽  
Printing Techniques

There are several ways of using three-dimensional printing techniques in the construction industry. One method that seems quite feasible is the concreting of walls and structural components starting at the bottom and progressing up in layers according to the principles of additive manufacturing. The goal of this study is to optimize the movements of a nozzle at one level that will result in this operation. This study considers that the movements of the nozzle can be of two types: rectangular only (i.e., only in x and y directions) or more freely, including moving in diagonal directions. Applications are performed on four hypothetical flats (with 7, 8, 14, and 31 walls, respectively) and a structural component with 17 members. It is shown that as the number of walls and members increase, the problem of optimizing the movements of the nozzle becomes increasingly difficult due to exponentially increasing path combinations. A comparison is presented in terms of the ratio of movements of the nozzle without concreting to total distances traveled. The optimization process is conducted using the Harmony Search algorithm with a special coding and encoding system.

scholarly journals Solving Cell Placement Problem Using Harmony Search Algorithms

2018 ◽  
Vol 8 (4) ◽  
pp. 3172-3176
Author(s):  
R. M. Al Qasem ◽  
S. M. Massadeh
Keyword(s):  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Harmony Search ◽  
Optimal Solution ◽  
Harmony Search Algorithm ◽  
Placement Problem ◽  
Solution Quality ◽  
Chip Design ◽  
Cell Placement ◽  
Placement Algorithm

Cell placement is a phase in the chip design process, in which cells are assigned to physical locations. A placement algorithm is a way that satisfies the objectives and minimizes the total area while keeping enough space for routing. Cell placement is an NP-complete problem of very large size. In order to solve this problem, diversified heuristic algorithms are used. In this work, a new algorithm is proposed based on the harmony search algorithm. The harmony search algorithm mimics music improvisation process to find the optimal solution. Cell placement problem has many constraints, so in this work, the harmony search algorithm is modified to adapt to these constraints. Experiment results show that this algorithm is efficient for solving cell placement and is characterized by good performance, solution quality and likelihood of optimality.

Harmony Search Algorithm

2017 ◽  
pp. 1-36 ◽  
Author(s):  
Alireza Askarzadeh ◽  
Esmat Rashedi
Keyword(s):  
Optimization Problems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Optimal Solution ◽  
Harmony Search Algorithm ◽  
Computational Time ◽  
Engineering Applications ◽  
Heuristic Search Algorithm ◽  
And Performance ◽  
Significant Attention

Harmony search (HS) is a meta-heuristic search algorithm which tries to mimic the improvisation process of musicians in finding a pleasing harmony. In recent years, due to some advantages, HS has received a significant attention. HS is easy to implement, converges quickly to the optimal solution and finds a good enough solution in a reasonable amount of computational time. The merits of HS algorithm have led to its application to optimization problems of different engineering areas. In this chapter, the concepts and performance of HS algorithm are shown and some engineering applications are reviewed. It is observed that HS has shown promising performance in solving difficult optimization problems and different versions of this algorithm have been developed. In the next years, it is expected that HS is applied to more real optimization problems.

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