Search Results - (( parameter optimization based algorithm ) OR ( a contribution function algorithm ))
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Enhancing Harmony Search Parameters Based On Step And Linear Function For Bus Driver Scheduling And Rostering Problems
Published 2018“…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia
Published 2024“…This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short-term daily electricity load in Peninsular Malaysia. …”
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Improved bacterial foraging optimization algorithm with machine learning driven short term electricity load forecasting: A case study in Peninsular Malaysia
Published 2024“…This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short‑term daily electricity load in Peninsular Malaysia. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…Secondly, a new DE algorithm (ARDE-SPX) is introduced that automatically adapts a repository of DE strategies and parameters control schemes to avoid the problems of stagnation and make DE respond to a wide range of function characteristics at different stages of evolutionary search. …”
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Parameter extraction of single, double, and three diodes photovoltaic model based on guaranteed convergence arithmetic optimization algorithm and modified third order Newton Raphson methods
Published 2022“…The proposed guaranteed convergence arithmetic optimization algorithm based on efficient modified third order Newton Raphson (GCAOAEmNR) method highlights important contributions to the literature in terms of methodology (explorer-exploiter phases) and objective function design. …”
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Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems
Published 2024“…The empirical assessment of these proposed methods encompasses a diverse set of 23 benchmark functions, demonstrating their efficacy comparable to well-established metaheuristic algorithms such as as the Grey Wolf Optimizer (GWO), Multi-Verse Optimization (MVO), Sine Cosine Algorithm (SCA), Ant Lion Optimizer (ALO), Moth-Flame Optimization Algorithm (MFO), and Grasshopper Optimization Algorithm (GOA). …”
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Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm
Published 2020“…Thus, a safe experimentation dynamics (SED) algorithm is selected to solve this unstable convergence but still not enough to achieve high accuracy because the update designed parameter only depends on the fixed step size gain. …”
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Discrete-time system identification using genetic algorithm with single parent-based mating technique
Published 2024“…This research makes several important contributions to the field of GA and SI. The introduction of the SPM technique represents a significant enhancement in the performance of GA, particularly in terms of improving genetic diversity and search optimization . …”
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Chaos search in fourire amplitude sensitivity test
Published 2012“…Work in Artificial Intelligence (AI) often involves search algorithms. In many complicated problems, however, local search algorithms may fail to converge into global optimization and global search procedures are needed. …”
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Chaos Search in Fourier Amplitude Sensitivity Test
Published 2012“…FAST was originally developed based on the Fourier series expansion of a model output and on the assumption that samples of model inputs are uniformly distributed in a high dimensional parameter space. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…A spatio-statistical optimization technique that combines the Taguchi statistical method and a spatial plateau objective function (POF) was presented to improve the segmentation procedures for building footprint extraction. …”
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Optimization of a robust sigmoid PID controller for automatic voltage regulation using the nonlinear sine-cosine algorithm with amplifier feedback dynamic weighted (AFDW) system
Published 2025“…The given paper presents a robust Sigmoid-based Proportional-Integral-Derivative (SPID) controller for Automatic Voltage Regulator (AVR) systems, optimized using the Nonlinear Sine Cosine Algorithm (NSCA) enhanced with the Amplifier Feedback Dynamic Weighted (AFDW) system. …”
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Optimization of supply chain management by simulation based RFID with XBEE Network
Published 2015“…This algorithm computes the optimal results of objective functions in a scientific manner. …”
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Green network planning and operational power consumption optimization in LTE-A using artificial intelligence
Published 2015“…A cascaded multi-objective genetic algorithm network optimization (CMOGANO) is developed to optimize the network number of base station, their location and configuration in the first stage to provide full coverage. …”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…The contribution of this work is to optimize the base of Fuzzy membership function of the APFLC by using GA technique. …”
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Mobility-aware Offloading Decision For Multi-access Edge Computing In 5g Networks
Published 2024journal::journal article -
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Optimal overcurrent relay coordination in wind farm using genetic algorithm
Published 2015“…GA was used to obtain improved values for each relay settings based on their coordination criteria. Each relay operation time and TSM are optimized which would contribute to provide a better protection for wind farm. …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network
Published 2023“…The review of optimization studies in the literature contributes to the development of a flowchart of an advanced optimization strategy that serves as a guide for the methodology of the study. …”
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Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios
Published 2015“…In order to increase the system efficiency and maximize the power generation, constructed operation models were optimized. To determine the optimum solution in each policy, real coded genetic algorithm is used as an optimization technique. …”
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