Alaa Ahmed Alzoubi

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Research

Comprehensive review of the development of the harmony search algorithm and its applications

Authors : Ala’a Alomoush, Abdulrahman A Alsewari, Hammoudeh S Alamri, Kamal Z Zamli

Abstract :This paper presents a comprehensive overview of the development of the harmony search (HS) algorithm and its applications. HS is a well-known human-based meta-heuristic algorithm that mimics the process of creating a new harmony in music. This algorithm can be applied to different fields of research, owing to its ability to balance between exploitation (i.e., searching around the known best) and exploration (i.e., roaming the entire search space). Thus, numerous studies have been conducted to utilize HS in real-world optimization problems, and many variants and hybrid algorithms of HS have been developed to cope with different problems. In this paper, HS and its variants are reviewed from various aspects. First, we describe the HS algorithm and present how its parameters affect algorithm performance. Second, we describe HS classifications based on the well-known HS variants and hybrid algorithms

Keywords : Harmony search, evolutionary algorithms, meta-heuristics, Optimization, computational intelligence

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Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning

Authors :Ala’a Alomoush, A. A. Alsewari, H. S. Alamri, K. S. Aloufi

Abstract :

Keywords : Computational intelligence, grey wolf optimizer, harmony search, hybrid algorithm, metaheuristic, optimization algorithm, CEC2014.

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Artificial bee colony algorithm for pairwise test generation

Authors :AK Alazzawi, AAB Homaid, Ala’a Alomoush, ARA Alsewari

Abstract :

Keywords : Artificial bee colony, evolutionary algorithms, pairwise test generation, meta-heuristics, Optimization, computational intelligence

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Modified opposition based learning to improve harmony search variants exploration

Authors : W Alomoush, A Alrosan, YM Alomari, AA Ala’a Alomoush Almomani, ...

Abstract :Image segmentation is the method of dividing an image into many segments, comprising groups of pixels. It is a process used to determine objects within the image. Fuzzy c-means (FCM) technique has been popularly employed as grayscale image segmentation method. Meanwhile, the conventional FCM suffers from some drawbacks including easy fall into local optimal solution resulting from inappropriate selection of the initial cluster center values and optimal number of clusters (regions) for each image without a prior knowledge or input by the operator. To solve FCM issues, the paper proposes a new fully automatic segmentation method for grayscale images based on fuzzy c-means with firefly mate algorithm (AUTO-FCM-FMA). This approach utilizes the mate list (M) mechanism with firefly algorithm (FMA) to search for the near-optimal number clusters, the location of centroids by exploring the search space and

Keywords :Image segmentation, Fuzzy c-means

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Fully automatic grayscale image segmentation based fuzzy C-means with firefly mate algorithm

Authors :W Alomoush, A Alrosan, YM Alomari, AA Ala’a Alomoush Almomani, ...

Keywords :Image segmentation, Fuzzy c-means

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Enhancing three variants of harmony search algorithm for continuous optimization problems

Authors : Ala’a Alomoush, ARA Alsewari, KZ Zamli, A Alrosan, W Alomoush, K Alissa

Abstract :Meta-heuristic algorithms are well-known optimization methods, for solving real-world optimization problems. Harmony search (HS) is a recognized meta-heuristic algorithm with an efficient exploration process. But the HS has a slow convergence rate, which causes the algorithm to have a weak exploitation process in finding the global optima. Different variants of HS introduced in the literature to enhance the algorithm and fix its problems, but in most cases, the algorithm still has a slow convergence rate. Meanwhile, opposition-based learning (OBL), is an effective technique used to improve the performance of different optimization algorithms, including HS. In this work, we adopted a new improved version of OBL, to improve three variants of Harmony Search, by increasing the convergence rate speed of these variants and improving overall performance. The new OBL version named improved opposition-based learning (IOBL), and it is different from the original OBL by adopting randomness to increase the solution's diversity. To evaluate the hybrid algorithms, we run it on benchmark functions to compare the obtained results with its original versions. The obtained results show that the new hybrid algorithms more efficient compared to the original versions of HS. A convergence rate graph is also used to show the overall performance of the new algorithms.

Keywords :Computational intelligence, harmony search, hybrid algorithm, metaheuristic, optimization algorithm, Opposition based learning.

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Solving 0/1 knapsack problem using hybrid HS and Jaya algorithms

Authors :Ala’a Alomoush, ARA Alsewari, HS Alamri, KZ Zamli

Abstract :Knapsack problem is a combinatorial optimization problem, where a fixed-size Knapsack must be filled with the most valuable items. Solving knapsack problem consider NP hard problem and many previous research tried to find optimal solution for it. In this research, a new hybrid algorithm of Harmony search and Jaya search algorithms applied on 0/1 Knapsack problem to find a near optimal results. HS algorithm has been modified to handle the 0/1 Knapsack problem, such as adding penalty function to cope the weight condition, exclude the harmony search bandwidth (bw) parameter, and use the current best result in the next iteration to obtain a better result. The new hybrid algorithm has been applied on different cases of Knapsack problem with different dimensions. 20 case studies have been evaluated by the new hybrid algorithm. The results obtained are competitive to previous HS variants that used to solve …

Keywords : Solving 0/1 knapsack problems, Harmony Search, Optimization algorithms

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Hyperdize jaya algorithm for harmony search algorithm’s parameters selection

Authors : Ala’a Alomoush, A Al-Sewari, B Ameen, S Hammoudeh, Z Kamal

Abstract :Abstract—this paper present a successful method to tune the parameters of the harmony search algorithm, which is a well-known meta-heuristic algorithm. Choosing the values of HS parameters consider as a difficulty when we use it in different cases, and we tried to solve this problem by using another meta-heuristic algorithm to pick the right value for one of these parameters, which is harmony memory consideration rate. To evaluate the performance of the amended algorithm, we have applied it on different bench-mark functions that shows its good performance, in terms of result accuracy in contrast with the original algorithm Harmony Search with less number of iterations, and when we compare it with two other well-known variants of HS.

Keywords :Jaya Algorithm, Harmony Search algorithm, continuous optimization problem

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Pressure Vessel Design Simulation Using Hybrid Harmony Search Algorithm

Authors : Ala’a Alomoush, MI Younis, KS Aloufi, ARA Alsewari, KZ Zamli

Abstract :Recently the development of optimization algorithm is rapidly increased. Among several optimization algorithms, Harmony Search (HS) has been recently proposed for solving engineering optimization problems. The HS has some weaknesses such as parameters selection and falling in local optima. Many variants proposed to solve these problems. This paper presents successful hybrid algorithms with high performance to solve the pressure vessel design simulation. The hybrid algorithms consist of well-known variants of HS and an opposition-based learning technique. The hybrid algorithm improved the HS exploration and avoiding falling in local optima, which lead the algorithm to provide significant results.

Keywords : Pressure Vessel Design; Harmony Search Algorithm; Optimization algorithm; hybrid algorithm; opposition-based learning; Computational Intelligence.

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An open cloud-based platform for the creation and delivery of smart applications and services

Authors : HM Fadhil, MI Younis, ARA Alsewari, M Abd-Alrazzaq, AT Mahdi, Ameer Toran Mahdi, Alaa A Alomoush

Abstract :With the increasing integration of computers and smartphones into our daily lives, in addition to the numerous benefits it offers over traditional paper-based methods of conducting affairs, it has become necessary to incorporate one of the most essential facilities into this integration; namely: colleges. The traditional approach for conducting affairs in colleges is mostly paper-based, which only increases time and workload and is relatively decentralized. This project provides educational and management services for the university environment, targeting the staff, the student body, and the lecturers, on two of the most used platforms: smartphones and reliable web applications by cloud hosting. The services include project management, attendance marking, various notifications and alerts, files and resources, a grading system, and an assignment management system. This paper also aims to ultimately digitalize most of …

Keywords : Smart Campus, Web Portal, Mobile Application, Cloud, IoT

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Software Testing for Internet of Things (IoT)

Authors : HS Alamri, Ala’a Alomoush, YA Alsaraira, KZ Zamli

Abstract :The Internet of Things (IoT) is growing so fast than ever. It’s going to have a huge impact on just about every market around the world within few years from now. So, it’s certainly possible to overlook some of the most important elements needed to effectively take advantage of this trend. Because the Internet of Things will be involved in many parts of our life such as cars, house, traffic, to name a few, that will make it so critical to be tested in the best way to avoid any kind of failure. Also, because the Internet of Things is complex and quickly evolving that will make software quality more important than ever. This paper highlight the software testing as a service for IoT.