Search Results - (( using function method algorithm ) OR ( software optimization search algorithm ))
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1
Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…Artificial Neural Networks (ANN) techniques, mostly Back-Propagation Neural Network (BPNN) algorithm has been used as a tool for recognizing a mapping function among a known set of input and output examples. …”
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Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions
Published 2022“…This paper aims to compare the performance of two metaheuristic algorithms which are Jaya Algorithm (JA) and Cuckoo Search (CS) using some common benchmark functions. …”
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Enhancing three variants of harmony search algorithm for continuous optimization problems
Published 2021“…A convergence rate graph is also used to show the overall performance of the new algorithms.…”
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Global gbest guided-artificial bee colony algorithm for numerical function optimization
Published 2018“…Numerous computational algorithms are used to obtain a high performance in solving mathematics, engineering and statistical complexities. …”
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Long term energy demand forecasting based on hybrid, optimization: Comparative study
Published 2012“…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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6
A comparative study of heuristic methods to solve Traveling Salesman Problem (TPS)
Published 2011“…The implementations of the three methods to solve TSP show that the RTS algorithm provides a better solution in terms of minimizing the objective function while SA algorithm is less time consuming in solving problem with large number of cities.In conclusion, RTS is more effective in producing good quality solution and on the other hand, SA may be used to obtain instant results.…”
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7
A modified n-th section line search in conjugate gradient methods for solving unconstrained optimization / Muhammad Imza Fakhri Jinudin
Published 2018“…All algorithms are written and executed using Maple 16 software. …”
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Evaluation of Search Result of Document Search Based GA (DSEGA)
Published 2004“…It is composed by a series of module that using information retrieval method and genetic algorithm. …”
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Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed
Published 2017“…The whole constraint analyzer and the fitness function were combined with four SBTs (genetic algorithm, evolutionary algorithm, simulating annealing, and quantum genetic algorithm). …”
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10
Hybrid optimization approach to estimate random demand
Published 2012“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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11
Simulation and design of A DC-DC synchronous converter by intelligent optimization techniques
Published 2010“…The derived optimal parameters of the converter from Genetic Algorithm method are compared with those obtained using the other two intelligent techniques.…”
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Sine-cosine optimization-based bijective substitution-boxes construction using enhanced dynamics of chaotic map
Published 2018“…This paper proposes a novel method of constructing strong substitution-boxes (S-boxes) of order n (4 ≤ n ≤ 8) based on a recent optimization algorithm known as sine-cosine algorithm (SCA). …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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Heuristic resource allocation algorithm for controller placement in multi-control 5G based on SDN/NFV architecture
Published 2021“…The integration of Software Defined Networking (SDN) and Network Function Virtualization (NFV) is considered to be an efficient solution that enables the forecasting of highly scalable, optimal performance of 5G networks by providing an effective means of network functionality. …”
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A Compromise Programming to Task Assignment Problem in Software Development Project
Published 2021“…The proposed method allows the incorporation of the model as a navigator for search agents in the optimal solution search process by transferring the objective function to the agents' fitness function. …”
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Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain
Published 2014“…After that a Meta-heuristic method is used for finding the global optimum solution. …”
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Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…Moreover, adaptive teaching learning-based optimization is used to search for near-optimal values for the four parameters of the COCOMO II model, which are then tested for validity on a software project of NASA. …”
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Cuckoo search algorithm as an optimizer for optimal reactive power dispatch problems
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