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1
Towards Software Product Lines Optimization Using Evolutionary Algorithms
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Proceeding Paper -
2
Maintain optimal configurations for large configurable systems using multi-objective optimization
Published 2022“…Hence, multiobjective evolutionary algorithms help to optimize the configuration process of SPL. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Software testing optimization for large systems using agent-based and NSGA-II algorithms
Published 2023“…Consequently, a multi-objective optimization technique can be used to optimize the large system testing process. …”
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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter
Published 2015“…This paper proposes three steps of improvements for identification of the nonlinear dynamic system, which exploits the concept of a state-space based time domain Volterra model. The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…Two multi-objective fed-batch models are also used as case studies to verify the performance of the proposed algorithm. …”
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Thesis -
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Optimization of micro-end milling process parameters of titanium alloy using non-dominated sorting genetic algorithm
Published 2013“…Finally, non-dominated sorting genetic algorithm-II as evolutionary optimization approach was used for multi-objective optimization of the micro-end milling process. …”
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8
Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem
Published 2017“…The proposed algorithm is evaluated using tasks scheduling in the scheduling load simulator and validated using statistical modeling. …”
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9
Staff scheduling for a courier distribution centre using evolutionary algorithm
Published 2022“…This paper proposed evolutionary algorithm, namely genetic algorithm as the solution to courier center staff scheduling. …”
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Article -
10
Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter
Published 2015“…This paper proposes three steps of improvements for identification of the nonlinear dynamic system, which exploits the concept of a state-space based time domain Volterra model. The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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Metaheuristic algorithms for feature selection (2014–2024)
Published 2025“…Over the last decade (2014–2024), numerous approaches have been explored, each with its own optimization strengths and constraints. Swarm intelligence and evolutionary algorithms—including genetic algorithms, particle swarm optimization, and the zebra optimization algorithm—have operated effectively in this area. …”
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Modelling business processes using evolutionary generated petri nets
Published 2017“…Evolutionary algorithms or computations (EC) are commonly used for solving problems such as optimization and reverse engineering of complex systems. …”
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Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…This thesis proposes the application of a stochastic optimization algorithm called Binary Particle Swarm Optimization algorithm for structure selection of polynomial NARX/NARMA/NARMAX models. …”
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Thesis -
15
Optimization of RFID network planning for monitoring railway mechanical defects based on gradient-based Cuckoo search algorithm
Published 2020“…For the second objective, the Analytic Hierarchy Process (AHP) was used to decide which stations can be used to monitor the railway system optimally. …”
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Thesis -
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An integrated reservoir modelling and evolutionary algorithm for optimizing field development in a mature fractured reservoir
Published 2016“…The second method is automatic optimization using Genetic Algorithm. That depends on the principle of natural selection as proposed by Darwin The genetic program was coupled with the reservoir flow model to re-evaluate the chosen wells at each iteration until obtaining the optimal choice. …”
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Conference or Workshop Item -
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Newton competitive genetic algorithm method for optimization the production of biochemical systems
Published 2018“…In this work, the optimization of biochemical systems production is performed by using a hybrid method of Newton competitive genetic algorithm is presented. …”
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A Newton Cooperative Genetic Algorithm Method for In Silico Optimization of Metabolic Pathway Production
Published 2015“…The NCGA used Newton method in dealing with the metabolic pathway, and then integrated genetic algorithm and cooperative co-evolutionary algorithm. …”
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Article -
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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…Metaheuristic parameter estimation is an algorithm framework that is processed using some technique to generate a pattern or graph. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…Evolutionary computation (EC) is known to be an effective search and optimization method and in this paper EC is proposed as a model structure selection algorithm. …”
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