Search Results - (( initial solution based algorithm ) OR ( data distribution function algorithm ))
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Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal
Published 2022“…In addition, objective function using the same CSSA algorithm were applied i.e., Vmin and Ploss as the objective function, and multi-objective involves Vmin and Ploss as the objective function. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering 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. The activation function in this neural network model then estimated using genetic algorithms. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…In general, genetic based clustering algorithms showed the ability to reach near global optimal solution. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…However, the current meta-heuristic algorithms do not ensure an optimum solution within a reasonable time. …”
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Garra Rufa‐inspired optimization technique
Published 2020“…Generally, in artificial intelligence optimization, the particles follow a local or global best particle until finding an acceptable solution. In welldeveloped optimization techniques, such as swarm optimization (PSO) and the firefly algorithm (FA), getting around the initial optimal value of the group and randomly checking the effect of the surrounding points may lead to a better solution than the initial optimal value. …”
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A controller-agnostic random oracle based intrusion detection method in software defined networks / Adnan
Published 2016“…All the hype surrounding the SDNs is predominantly because of its centralized management functionality, the separation of the control plane from the data forwarding plane, and enabling innovation through network programmability. …”
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Design and statistical analysis of initial solution construction approach in curriculum based course timetabling problem
Published 2017“…To produce a population of initial solution require algorithm that can produce multiple feasible solutions and these solutions must be diverse. …”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…Firstly, an architecture for the clustering ensemble based on incremental genetic-based algorithms is proposed consisting of two phases: (i) to produce cluster partitions as initial populations, (ii) to combine cluster partitions and to generate final clustering solution by incremental genetic based clustering ensemble learning algorithm. …”
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Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…A heuristic algorithm was introduced to generate the initial population for intelligence based genetic algorithm. …”
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Enhancing the Sorting Layers in the Initial Stage of High School Timetabling
Published 2020“…KHE is an algorithm that generates initial solution of HSTP. …”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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Optimizing S-box generation based on the Adaptive Agent Heroes and Cowards Algorithm
Published 2021“…This paper introduces a new variant of a metaheuristic algorithm based on Agent Heroes and Cowards Algorithm (AHC), called Adaptive Agent Heroes and Cowards Algorithm (AAHC). …”
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Construction of initial solution population for curriculum-based course timetabling using combination of graph heuristics
Published 2016“…The construction of population of initial solution is a crucial task in population-based metaheuristic approach for solving curriculum-based university course timetabling problem because it can affect the convergence speed and also the quality of the final solution.This paper presents an exploration on combination of graph heuristics in construction approach in curriculum based course timetabling problem to produce a population of initial solutions.The graph heuristics were set as single and combination of two heuristics.In addition, several ways of assigning courses into room and timeslot are implemented.All settings of heuristics are then tested on the same curriculum based course timetabling problem instances and are compared with each other in terms of number of population produced.The result shows that combination of largest degree followed by saturation degree heuristic produce the highest number of population of initial solutions.The results from this study can be used in the improvement phase of algorithm that uses population of initial solutions…”
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Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences
Published 2021“…These algorithms can affect convergence to identify a robust optimum solution. …”
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Vehicle Routing Problem with Simultaneous Pickup and Delivery
Published 2020“…A simple heuristic is used to generate the initial solution in the first phase. Then, the feasible solution obtained in the first phase will become the initial input for the improvement phase, which applied the VNS algorithm. …”
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Study on numerical solution of a variable order fractional differential equation based on symmetric algorithm
Published 2019“…As the class of fractional differential equations with changing order has attracted more attention and attention in the fields of research and engineering, it is important to study its numerical solutions. Numerical solution algorithm for a class of fractional differential equations with transformed arrays based on the proposed symmetry algorithm. …”
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Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm
Published 2018“…In the hierarchical Bayesian approach, the order and coefficients of the autoregressive model are assumed to have a prior distribution. The prior distribution is combined with the likelihood function to obtain a posterior distribution. …”
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