Search Results - (( evolution optimisation based algorithm ) OR ( using interactive bee algorithm ))

Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage by Huy P.D., Ramachandaramurthy V.K., Yong J.Y., Tan K.M., Ekanayake J.B.

Sequence-based interaction testing implementation using Bees Algorithm by Mohd Hazli M.Z., Kamal Z. Z., Rozmie R. O.

“…In this paper we present a sequence-based interaction testing strategy (termed as sequence covering array) using Bees Algorithm. …”

Hybrid Artificial Bee Colony Algorithm for t-Way Interaction Test Suite Generation by Alazzawi, A.K., Rais, H.M., Basri, S.

“…This is called hybrid artificial bee colony (HABC) strategy, which is based on hybridize of an artificial bee colony (ABC) algorithm with a particle swarm optimization (PSO) algorithm. …”
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Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design by Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Mohd Zaidi, Mohd Tumari

“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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Implementing a T-Way Test Generation Strategy Using Bees Algorithm by Mohd Hazli, Mohamed Zabil, Kamal Z., Zamli

“…Highly customizable software allow users to configure the software to the users’ needs, however, if not tested adequately, these software are prone to interaction faults. This paper discusses our experiences on implementation of Bees algorithm for generating test cases to detect t-way interaction faults (where t signifies the interaction strength). …”
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A competitive co-evolutionary approach for the nurse scheduling problem by Mohamad Nazri, Maizatul Farhana, Mohd Yusoh, Zeratul Izzah, Basiron, Halizah, Daud, Azlina

“…The competitive approach further exhibits smoother convergence behaviour across generations, indicating stronger optimisation dynamics and improved robustness. These findings demonstrate that competitive co-evolution provides an effective and practical alternative to static fitness-based evolutionary methods for nurse scheduling, with broader applicability to healthcare scheduling and constraint optimisation problems.…”
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Implementing a t-way test generation strategy using bees algorithm by Zabil M.H.M., Zamli K.Z.

“…Highly customizable software allow users to configure the software to the users' needs, however, if not tested adequately, these software are prone to interaction faults. This paper discusses our experiences on implementation of Bees algorithm for generating test cases to detect t-way interaction faults (where t signifies the interaction strength). © SCRG Publication, 2013.…”

Adopting Bees Algorithm for Sequenced Based T-Way Test Data Generation by Kamal Z., Zamli, Mohd Hazli, Mohammed Zabil

“…Despite being very useful, those strategies have assumed sequence-less interaction among the input-values. …”
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Test Data Generation for Event Driven System Using Bees Algorithm by Mohammed Zabil, Mohd H., Kamal Z., Zamli

“…In this paper we discuss and proposed a new strategy for generating test data for event-driven system using a bio inspired artificial intelligent, namely Bees Algorithm (BA). …”
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Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation by M. H., Mohamed Zabil, Kamal Z., Zamli, K. C., Lim

“…T-way testing is a testing technique that is used to detect faults due to parameter interactions or software configurations. …”
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HABC: Hybrid artificial bee colony for generating variable T-way test sets by Alazzawi, A.K., Rais, H.M., Basri, S.

“…The input variables for a realworld software may diverge in how they strongly influence variable strength (VS) interaction can achieve that effectively. This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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HABC: Hybrid artificial bee colony for generating variable T-way test sets by Alazzawi, A.K., Rais, H.M., Basri, S.

“…The input variables for a realworld software may diverge in how they strongly influence variable strength (VS) interaction can achieve that effectively. This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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Pairwise Test Suite Generation Based on Hybrid Artificial Bee Colony Algorithm by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A.

“…Complementing to the earlier researches, this paper proposes a new pairwise test suite generation called Pairwise Hybrid Artificial Bee Colony (PhABC) strategy based on hybridize of an Artificial Bee Colony (ABC) algorithm with a Particle Swarm Optimization (PSO) algorithm. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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A hybrid of integer differential bees and flux balance analysis for improving succinate and lactate production by Arieef, Mohd Fahmi, Yee, Wen Choon, Mohamad, Mohd Saberi, Deris, Safaai, Napis, Suhaimi, Kasim, Shahreen

“…However, the previous works were ineffective to produce the highest production due to the size and complexity of metabolic networks and the dynamic interaction between the components. Therefore, the main purpose of this study is to overcome the limitation of the existing algorithms which hybridizing Integer Differential Bees and Flux Balance Analysis (IDBFBA). …”
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A hybrid of integer differential bees and flux balance analysis for improving succinate and lactate production by Arieef, Mohd Fahmi, Kasim, Shahreen, Yee, Wen Choon, Mohamad, Mohd Saberi, Deris, Safaai, Napis, Suhaimi, Kasim, Shahreen

“…However, the previous works were ineffective to produce the highest production due to the size and complexity of metabolic networks and the dynamic interaction between the components. Therefore, the main purpose of this study is to overcome the limitation of the existing algorithms which hybridizing Integer Differential Bees and Flux Balance Analysis (IDBFBA). …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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T-way strategy for sequence input interactions test case generation adopting fish swarm algorithm by Rahman, Mostafijur, Sultana, Dalia, Sabira, Khatun, M. F. M., Jusof, Syamimi Mardiah, Shaharum, Nurhafizah, Abu Talip Yusof, Qaiduzzaman, Khandker M., Hasan, Md. Hasibul, Rahman, Md. Mushfiqur, Hossen, Md. Anwar, Begum, Afsana

“…In order to reduce test cases several T-way sequence input interaction strategies are explored, such as, Bee Algorithm(BA), Kuhn encoding (K) , ASP with Clasp , CP with Sugar, Erdem (ER) exact encoding, Tarui (TA) Method, U, UR, D and DR, Brain (BR). …”
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