Search Results - (( using factor problem algorithm ) OR ( evolution optimisation based algorithm ))
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Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design
Published 2014“…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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A competitive co-evolutionary approach for the nurse scheduling problem
Published 2026“…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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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…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 hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…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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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…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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Book Section -
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B-spline curve fitting with different parameterization methods
Published 2020“…After generating control points, distance between the generated and original data points is used to identify the error of the algorithm. Later, genetic algorithm and differential evolution optimization are used to optimise the error of the curve. …”
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Final Year Project / Dissertation / Thesis -
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Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods
Published 2017“…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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Heuristic factors in ant system algorithm for course timetabling problem
Published 2009“…This paper presents an algorithm that is based on ant system to solve the course timetabling problem.The problem is modeled using the bipartite graph.Four heuristic factors are derived from the graph characteristic, are used to direct ants as the agent in finding course timetable elements The concept of negative pheromone was also applied to ensure that paths leading to dead ends are not chosen.The performance of this proposed algorithm is promising when comparison of performance was made with the original ant system algorithm. …”
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Conference or Workshop Item -
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Enhancement of Ant System Algorithm for Course Timetabling Problem
Published 2009“…As the requirement of the Ant System Algorithm, the problem is modeled as a graph that can be used by the ant to deliver its pheromone. …”
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iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems
Published 2024“…In addition, a new optimisation model for finding optimum parameter values in the MEDF and an algorithm for transmuting a 1D quantitative feature into a respective categorical feature are developed to facilitate the model. …”
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Modification of the ant colony optimization algorithm for solving multi-agent task allocation problem in agricultural application
Published 2024“…Simulation results showed that the proposed ACO algorithm with the modified efficiency factor improved the performance of basic ACO algorithm for solving task allocation problem in terms of the average total travel cost for each agent. …”
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A new cryptographic algorithm based on decomposition problem in elliptic curve cryptography / Hilyati Hanina Zazali
Published 2012“…Since subexponential-time algorithm is known for ordinary discrete logarithm problem and integer factorization problem and not for elliptic curve discrete logarithm problem, the algorithm presented for the digital signature in this study has substantially greater strength per key bit than in other digital signature algorithm…”
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Three-term backpropagation algorithm for classification problem
Published 2006“…Standard Backpropagation Algorithm (BP) is a widely used algorithm in training Neural Network that is proven to be very successful in many diverse application. …”
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Factors and types of error that contributes to the difficulties in solving Mathematical problems among Year 5 pupils in SK Goebilt, Kuching / Hardi Rasidi
Published 2016“…The objectives of this research are to identify the factors and types of algorithm error that contributes to difficulties in solving mathematical word problems. …”
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Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat
Published 2020“…In this study, the problem of determination dengue disease factors was modeled using a neural network. …”
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Tiki-taka algorithm: a novel metaheuristic inspired by football playing style
Published 2021“…The algorithm was tested using 19 benchmark functions and five engineering design problems. …”
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Multi-objective constrained algorithm (MCA) and non-dominated sorting genetic algorithm (NSGA-ii) for solving multi-objective crop planning problem
Published 2016“…In this paper, we formulate a crop planning problem as a multiobjective optimization model and try to solve two different versions of the problem using two different optimization algorithms MCA and NSGA. …”
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Optimization of ship routing using hybrid genetic algorithm / Ismail
Published 2014“…Soft constraints concerns with ship draft and load factor. To solve this problem, we propose a hybrid genetic algorithm (hybrid GA). …”
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