Search Results - (( java implication based algorithm ) OR ( using interactive ant algorithm ))

Interacted Multiple Ant Colonies for Search Stagnation Problem by Aljanabi, Alaa Ismael

“…This thesis addresses the issues associated with search stagnation problem that ACO algorithms suffer from. In particular, it proposes the use of multiple interacted ant colonies as a new algorithmic framework. …”
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An exploration technique for the interacted multiple ant colonies optimization framework by Aljanaby A., Ku-Mahamud K.R., Norwawi N.Md.

Stagnation control using interacted multiple ant colonies by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md Norwawi, Norita

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Analysis of the stagnation behavior of the interacted multiple ant colonies optimization framework by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana

“…The framework of Interacted Multiple Ant Colonies Optimization (IMACO) is a recent proposition.It divides the ants’ population into several colonies and employs certain techniques to organize the work of these colonies.This paper conducts experimental tests to analyze the stagnation behavior of IMACO.It also proposes the idea that different ant colonies use different types of problem dependent heuristics.The performance of IMACO was demonstrated by comparing it with the Ant Colony System (ACS) the best performing ant algorithm.The Computational results show the superiority of IMACO. …”
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An exploration technique for the interacted multiple ant colonies optimization framework by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md. Norwawi, Norita

“…In this framework several colonies of artificial ants are utilized. These colonies are working coopereatively to solve an optimization problem using some interaction technique. …”
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An Exploration Technique for the Interacted Multiple Ant Colonies Optimization Framework by Aljanaby, A, Ku-Mahamud, KR, Norwawi, NM

“…These tests also show the capability of IMACO to outperform other well known ant algorithms like ant colony system and max-min ant system.…”

Interacted multiple ant colonies optimization approach for the single machine total weighted tardiness problem by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana

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A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots by Ismail, Amelia Ritahani, Tumian, Afidalina

“…According to [13], the two best-known swarm intelligence algorithms are Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO). …”
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A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali by Mohamed Kamali, Mohd Zahurin

“…In this thesis, we implement the modified ant colony programming (ACP) algorithm for solving the matrix Riccati differential equation (MRDE). …”
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A comparative study on testing optimization techniques with combinatorial interaction testing for optimizing software product line testing by Maidin, Nur Farrahin, Hassan, Sa’Adah, Baharom, Salmi, Md. Sultan, Abu Bakar

“…The optimization algorithms we explored are the Genetic Algorithm, Cuckoo Search algorithm, Ant Colony algorithm, and Particle Swarm Optimization algorithm. …”
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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.

“…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing by S. Ahmed, Bestoun

“…Recently, researchers have started to explore the use of Artificial Intelligence (AI)-based algorithms as t-way (where t indicates the interaction strength) and variable-strength testing strategies. …”
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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). …”
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Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm by Mohammed Abdullah, Abdullah Nasser

“…Although useful, all aforementioned t-way strategies have assumed sequence-less interactions amongst input parameters. …”
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Solving large-scale problems using multi-swarm particle swarm approach by Salih, Sinan Q., Alsewari, Abdulrahman A.

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A review on autonomous mobile robot path planning algorithms by Noraziah, Adzhar, Yuhani, Yusof, Muhammad Azrin, Ahmad

“…In this paper, commonly use classical approaches such as cell decomposition (CD), roadmap approach (RA), artificial potential field (AFP), and heuristics approaches such as genetic algorithm (GA), particle swarm optimization (PSO) approach and ant colony optimization (ACO) method are considered.It is observed that when it comes to dynamic environment where most of the information are unknown to the mobile robots before starting, heuristics approaches are more popular and widely used compared to classical approaches since it can handle uncertainty, interact with objects and making quick decision. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Recent advances of whale optimization algorithm, its versions and applications by Alyasseri Z.A.A., Ali N.S., Al-Betar M.A., Makhadmeh S.N., Jamil N., Awadallah M.A., Braik M., Mirjalili S.

“…One of the SI algorithms is called the whale optimization algorithm (WOA). …”

Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar by Abu Bakar, Nordin (Prof. Madya Dr.)

“…There is a model that studies the social behavior of humans called genetic algorithms (GA). An artificial neural network uses brain as a model to map decisions out of several inputs. …”
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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). …”
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