Search Results - (( simulation optimization system algorithm ) OR ( variable evaluation based algorithm ))
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Performance Evaluation of Vector Evaluated Gravitational Search Algorithms Based on ZDT Test Functions
Published 2014“…This paper presents a performance evaluation of Vector Evaluated Gravitational Search Algorithm (VEGSA), namely VEGSA-I and VEGSA-II algorithms, for multi-objective optimization problems. …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…Several research efforts have been developed to generate optimal operation rules for dam and reservoir systems utilizing different optimization algorithms. …”
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An improved particle swarm optimization based maximum power point tracking strategy with variable sampling time
Published 2015“…The performance of the proposed system is evaluated using MATLAB simulation and experimentation, in which a digital signal controller is used to implement the proposed algorithm on a real boost converter connected to a PV simulator. …”
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio...
Published 2023“…Comparing this developed algorithm with other algorithms shows its superiority in multi-objective optimization (MOO) evaluation metrics. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…System identification is a method of determining a mathematical relation between variables and terms of a process based on observed input-output data. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Optimal placement of unified power flow controller by dynamic implementation of system-variable-based voltage-stability indices to enhance voltage stability
Published 2016“…The locations of UPFC are identified by dynamically varying loads across all the PQ buses by different percentages to satisfy the real power system conditions. The simulations are conducted in a power system computer-aided design (PSCAD) environment where IEEE-39 bus system has been chosen as case study. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Finally, an adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order to increase the optimality and stability rates of the proposed path planning algorithm. …”
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Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement
Published 2023“…accuracy assessment; algorithm; control system; experimental study; instrumentation; optimization; performance assessment; simulation; algorithm; article; fuzzy logic; lightning; motor performance; simulation; velocity…”
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Low Complexity Error Correction in Low Density Parity Check (LDPC) Code Decoder and Encoder for Decode and Forward Cooperative Wireless Communication
Published 2021“…By using the optimization min-sum belief propagation approach, a low complexity min-sum (MS) based decoding algorithm called Variable Global Optimization Min-Sum (VGOMS) has been developed. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…This approach demonstrates the ability of the GOOSE algorithm to simulate complex systems and enhances the robustness and adaptability of the simulation tool by integrating essential behaviours into the computational framework. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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Optimizing energy and reserve minimization in a sustainable microgrid with electric vehicle integration: dynamic and adjustable manta ray foraging algorithm
Published 2023“…This paper presents a novel approach for optimizing energy and reserve minimization in a sustainable integrated microgrid with electric vehicles (EVs) by the use of the dynamic and adjustable Manta Ray Foraging (DAMRF) algorithm. …”
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Optimized fuzzy logic sliding mode control with proportional-integral-derivative for an electrohydraulic actuator system
Published 2023“…Due to the difficulty of concurrent hybrid design, the PSO algorithm was employed to determine the optimal control variables value. …”
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…IFS served as filter together with an Ant Colony Optimization System (ACO) as a metaheuristic form the hybrid system. …”
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New synchronization protocol for distributed system with TCP extension
Published 2013“…The resulting algorithm does not involve variability in the hardware type nor is it based on specific distributed application software or databases. …”
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Mobile data gathering algorithms for wireless sensor networks
Published 2014“…In this research, a Mobile Data Gathering based Network Layout (MDG-NL) algorithm is proposed. …”
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Capacity planning for mixed-load tester under demand and testing time uncertainty
Published 2018“…Currently,the company’s issue is low tester utilization of about 71%,well below the target of 96%.The objective of this research is to improve tester utilization while achieving the production target under uncertain demand and testing time and also to determine the break-even point on the testers required.A novel approach of integrating a mathematical model,robust optimization model,genetic algorithm,simulation model and cost–volume –profit analysis was developed.Firstly,a mathematical model of mixed-load tester was formulated.Next,a set of discrete scenarios was proposed to address uncertain demand and testing time.A robust optimization and genetic algorithm model was developed to optimize the number of testers under the described uncertainties.Next,these scenarios were simulated using the Pro Model simulation software to validate the proposed models and to evaluate throughput and tester utilization.Finally,the cost–volume–profit analysis was performed for scenarios that require additional testers at various levels of uncertainties.The results showed that the proposed solution improved tester utilization by 25% compared to the current system.This research has contribution by developing novel hybrid methodology and able to provide useful insights to assist company’s managers to plan and allocate resources according to variations in customers’ demands and testing time.…”
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