Search Results - (( sequence optimization means algorithm ) OR ( sequence optimisation based algorithm ))
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Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam
Published 2023“…The Whale Optimisation Algorithm (WOA), Harris Hawks Optimisation (HHO) Algorithm, Lévy Flight WOA (LFWOA) and the Opposition-Based Learning of HHO (OBL-HHO) were proposed to simulate the initial model’s response and optimise the Klang Gate Dam (KGD) release operation with observed inflow, water level (storage), release, and evaporation rate (loss). …”
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A headway and order scheme based mixed integer goal programming model for railway rescheduling / Zuraida Alwadood
Published 2017“…The headway restriction is formulated based on a new concept of blockoriented headway, whereas the sequence order is formulated based on the priority of conflicting trains. …”
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3
Optimisation of energy efficient Assembly Sequence Planning using Moth-Flame Optimisation alghorithm
Published 2019“…For optimisation purpose, this research proposed a relatively new algorithm called the Moth-Flame Optimisation (MFO). …”
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4
Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation
Published 2013“…The aim of this research is to establish a methodology and algorithm for integrating ASP and ALB optimisation using Particle Swarm Optimisation. …”
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5
An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite
Published 2018“…If t-way strategies are to be adopted in such a system, there is also a need to support test data generation based on sequence of interactions. In line with such a need, this paper presents a unified strategy based on the new meta-heuristic algorithm, called the elitist flower pollination algorithm (eFPA), for sequence and sequence-less coverage. …”
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6
An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design
Published 2014“…In literature, ACS has been employed to solve DNA sequence design problem. The DNA sequence design problem was modelled based on a finite state machine in which the nodes represent the DNA bases {A, C, T, G}. …”
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Modified Harris Hawks Optimization Algorithm For Protein Multiple Sequence Alignment
Published 2024“…A notable entrant in this domain is the harris hawks optimization (hho) algorithm, which has distinguished itself through published optimization outcomes, positioning it as a formidable competitor among state-of-the-art metaheuristics. …”
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9
An improved particle swarm optimization algorithm for data classification
Published 2023“…Particle Swarm Optimization (PSO) is a metaheuristic algorithm based on swarm intelligence, widely used to solve global optimisation problems throughout the real world. …”
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Linear-PSO with binary search algorithm for DNA Motif Discovery / Hazaruddin Harun
Published 2015“…Particle Swarm Optimisation (PSO) was selected as the base algorithm that needs improvement and integration with other techniques. …”
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Linear-pso with binary search algorithm for DNA motif discovery / Hazaruddin Harun
Published 2015“…Particle Swarm Optimisation (PSG) was selected as the base algorithm that needs improvement and integration with other techniques. …”
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A Study of the Contribution of Nearest-Neighbour Thermodynamic Parameters to the DNA Sequences Generated by Ant Colony Optimisation
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Energy efficient modeling and optimization for assembly sequence planning using moth flame optimization
Published 2019“…The problem was then optimized using moth flame optimization (MFO) and compared with well-established algorithms such as genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO). …”
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Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…Then, it started to find the best sequence of jobs for each line based on the generated population by heuristic algorithm. …”
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Effect of adopting different dispatching rules on the mean flow time in a two machine batch-shop problem
Published 2005“…Therefore, researchers concentrated on developing branch-and-bound or heuristic algorithms. Ali Allahverdi, 1998 obtained the optimal solutions for minimizing mean flow time in a two-machine flow shop with Sequence-independent set up times by using three heuristic algorithms. …”
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16
Biogeography based optimization (BBO) algorithm to minimise non-productive time during hole-making process
Published 2015“…The proposed approach tackles the sequencing problem when several holes must be drilled by means of different tools to reach their desired size. …”
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Flock optimization algorithm-based deep learning model for diabetic disease detection improvement
Published 2024“…The collected data is processed by a Gaussian filtering approach that eliminates irrelevant information, reducing the overfitting issues. Then flock optimization algorithm is applied to detect the sequence; this process is used to reduce the convergence and optimization problems. …”
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NARX modelling for steam distillation pilot plant using binary particle swarm optimisation technique / Najidah Hambali
Published 2019“…The model structure selection of polynomial NARX had been focused on Binary Particle Swarm Optimisation (BPSO) algorithm. The proposed NARX-based BPSO algorithm was implemented for both time-varying water and steam temperature from the SDPP. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…Hence, VLSI floorplanning is important in IC design. Floorplanning optimization consists of representation and optimization algorithm. …”
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20
A neural network modal decomposition mechanism in predicting network traffic
Published 2023“…Specifically, the predictive accuracy indexes such as Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) can reach a lowest optimum value of 1.1410, 0.1758 and 0.2263, and the average training time is reduced by 25.25%, 23.87% and 41.36%, respectively. …”
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