Hyperdize Jaya Algorithm for Harmony Search Algorithm's Parameters Selection by Alaa A., Al-Omoush, Al-Sewari, Abdul Rahman Ahmed Mohammed, Ameen, Bahomaid, Alamri, Hammoudeh S., Kamal Z., Zamli

“…This paper present a successful method to tune the parameters of the harmony search algorithm, which is a well-known meta-heuristic algorithm. …”
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Comprehensive review of the development of the harmony search algorithm and its applications by Al-Omoush, A.A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Kamal Z., Zamli

“…This paper presents a comprehensive overview of the development of the harmony search (HS) algorithm and its applications. …”
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Modified Opposition Based Learning to Improve Harmony Search Variants Exploration by Al-Omoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Kamal Z., Zamli

“…Harmony Search Algorithm (HS) is a well-known optimization algorithm with strong and robust exploitation process. …”
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Pressure vessel design simulation using hybrid harmony search algorithm by Alaa A., Alomoush, Mohammed I., Younis, Khalid S., Aloufi, Alsewari, Abdulrahman A., Kamal Z., Zamli

“…Among several optimization algorithms, Harmony Search (HS) has been recently proposed for solving engineering optimization problems. …”
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Enhancing three variants of harmony search algorithm for continuous optimization problems by Alomoush, Alaa A., Alsewari, Abdulrahman A., Kamal Z., Zamli, Alrosan, Ayat, Alomoush, Waleed, Alissa, Khalid

“…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. …”
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Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Aloufi, Khalid, Kamal Z., Zamli

“…Most metaheuristic algorithms, including harmony search (HS), suffer from parameter selection. …”
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Towards Supporting Input-Output Relation within Harmony Search Strategy for T-Way Testing by Al-Sewari, Abdulrahman A., Kamal Z., Zamli, Mohd Hafiz, Mohd Hassin

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Software product line test list generation based on harmony search algorithm with constraints support by Alsewari, Abdulrahman A., Kabir, M. Nomani, Kamal Z., Zamli, Alaofi, Khalid S.

“…Thus, the current study is aimed to develop a new SPL test list generation strategy based on Harmony Search (HS) algorithm, namely SPL-HS. SPL-HS generates a minimum number of test cases that cover all of the features that are required to be tested based on the required interaction degree (t). …”
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One Parameter at a time Combinatorial Testing Strategy Based on Harmony Search Algorithm OPAT-HS by Al-Sewari, Abdul Rahman Ahmed Mohammed, Mu’aza, Aminu Aminu, Rassem, Taha H., Tairan, Nasser M., Shah, Habib, Kamal Z., Zamli

“…Therefore, this paper will propose a new OPAT strategy based on Harmony Search Algorithm (HS) called OPAT-HS. OPAT-HS was originally designed only to support Covering Array (CA) and Mixed Covering Array (MCA) for uniform interaction strength. …”
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Comparative Performance Analysis of Flower Pollination Algorithm and Harmony Search based strategies: A Case Study of Applying Interaction Testing in the Real World by Nasser, Abdul B., Alsewari, Abdulrahman A., Mu’azu, Aminu A., Kamal Z., Zamli

“…In this paper, we present a comparison between two strategies, Harmony Search (HS) and Flower Pollination Algorithm (FPA) based strategies. …”
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Solving 0/1 Knapsack Problem Using Hybrid HS and Jaya Algorithms by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Kamal Z., Zamli

“…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. …”
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On Test Case Generation Satisfying the MC/DC Criterion by Kamal Z., Zamli, Al-Sewari, Abdul Rahman Ahmed Mohammed, Mohd Hafiz, Mohd Hassin

“…Complementing existing work and in line with the current trends, this paper justifies on the development of a Harmony Search based test generation strategy for satisfying the MC/DC criterion. …”
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An Orchestrated Survey on T-Way Test Case Generation Strategies Based on Optimization Algorithms by Alsewari, Abdulrahman A., Kamal Z., Zamli

“…This paper presents an orchestrated survey of the existing OpA t-way strategies as Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Algorithm (ACA), Particle Swarm Optimization based strategy (PSTG), and Harmony Search Strategy (HSS). The results demonstrate the strength and the limitations of each strategy, thereby highlighting possible research for future work in this area.…”
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An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite by Abdullah, Nasser, Kamal Z., Zamli, Alsewari, Abdulrahman A., Ahmed, Bestoun S.

“…In line with the upcoming of a new field called search-based software engineering (SBSE), many newly developed t-way strategies adopting meta-heuristic algorithms can be seen in the literature for constructing interaction test suite (such as simulated annealing (SA), genetic algorithm (GA), ant colony optimisation algorithm (ACO), particle swarm optimisation (PSO), harmony search (HS) and cuckoo search (CS). Although useful, most of the aforementioned t-way strategies have assumed sequence-less interactions amongst input parameters. …”
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Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions by Mazlina, Abdul Majid, Alsariera, Yazan A., Alamri, Hammoudeh S., Nasser, Abdullah M., Kamal Z., Zamli

“…Over the last 30 years, many meta-heuristic algorithms have been developed in the literature including that of Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search Algorithm (HS) to name a few. In order to help engineers make a sound decision on the selection amongst the best meta-heuristic algorithms for the problem at hand, there is a need to assess the performance of each algorithm against common case studies. …”
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An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation by Kamal Z., Zamli, Fakhrud, Din, Kendall, Graham, Ahmed, Bestoun S.

“…Recently, many meta-heuristic algorithms have been proposed to serve as the basis of a t-way test generation strategy (where t indicates the interaction strength) including Genetic Algorithms (GA), Ant Colony Optimization (ACO), Simulated Annealing (SA), Cuckoo Search (CS), Particle Swarm Optimization (PSO), and Harmony Search (HS). Although useful, meta-heuristic algorithms that make up these strategies often require specific domain knowledge in order to allow effective tuning before good quality solutions can be obtained. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

“…Genetic Algorithm (GA), Ant Colony (AC), Simulated Annealling (SA), Particle Swarm Optimization, and Harmony Search Algorithm (HS) as their basis in an effort to generate the most optimal solution. …”
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A new variable strength t-way strategy based on the cuckoo search algorithm by Abdullah, Nasser, Kamal Z., Zamli

“…Owing to its performance, the metaheuristicbased t-way strategies have gained significant attention recently (e.g., Particle swarmoptimization, genetic algorithm, ant colony algorithm, harmony search, and cuckoo search). Despite much progress, existing strategies have not sufficiently dealt with more than one interaction between input parameters (termed variable strength tway). …”
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A kidney algorithm with elitism for combinatorial testing problem by Bahomaid, Ameen A., Alsewari, Abdulrahman A., Kamal Z., Zamli, Alhendawi, Kamal M., Al-Janabi, Ala Aldeen

“…Kidney algorithm (KA) is a recent computational AI algorithm with sufficient optimization capability which outperforms the other AI algorithms (such as Genetic Algorithm (GA), Cuckoo Search (CS), Particle Swarm Optimization (PSO), Harmony Search (HS)) from some aspects. Although, KA may be easy to fall into local optima by keeping the worst solutions from the past generation as a new population with the best solutions. …”
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Latin hypercube sampling Jaya algorithm based strategy for T-way test suite generation by Nasser, Abdullah B., Abdul-Qawy, Antar S. H., Abdullah, Nibras, Hujainah, Fadhl, Kamal Z., Zamli, Ghanem, Waheed A. H. M.

“…Particle Swarm Optimization, Genetic Algorithm, Ant Colony Algorithm, Harmony Search, Jaya Algorithm and Cuckoo Search). …”
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