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1
Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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2
Advancing voltage control in DC microgrids: a comparative study with IGWO-based H∞ control
Published 2024“…However, nonlinear loads, like constant power loads (CPLs), can cause instability in DC-MGs and result in a voltage drop in the primary DC bus. This paper proposes the utilization of an Improved gray Wolf Optimization (IGWO) algorithm-based H-infinity (H∞) control approach to enhance traditional droop control techniques and address instability concerns. …”
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3
Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
4
Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam
Published 2023“…However, due to the drawbacks of the conventional algorithm as well as the heuristic algorithms handling complicated and multi-objective reservoir optimisation, the advantages of the strategy of simultaneous exploration and exploitation led to the decision to utilise meta-heuristic algorithms in this study. …”
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5
On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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Opposition-based spiral dynamic algorithm with an application to optimize type-2 fuzzy control for an inverted pendulum system
Published 2022“…Spiral Dynamic Algorithm (SDA) is a group-based optimization algorithm formulated based on the concept of a natural spiral phenomenon on earth. …”
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7
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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8
Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing
Published 2017“…In this paper, we combined MBO and elitism to solve the Combinatorial Interaction Testing (CIT) problem i.e. to find a set of minimum test case which is an NP-Complete problem. This proposed strategy is the first to utilize population based metaheuristic algorithm i.e. …”
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9
An adaptively switching iteration strategy for population based metaheuristics / Nor Azlina Ab. Aziz
Published 2017“…Experiments conducted using three parent algorithms namely particle swarm optimization (PSO), which is a popular population-based optimizer with population and individual memories, gravitational search algorithm (GSA), a memoryless young optimizer, and simulated Kalman filter (SKF), a newly introduced optimization algorithm that use population’s memory to guide an agent’s search, show that iteration strategy is an algorithm dependent parameter as well as function dependent. …”
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10
A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
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11
An Orchestrated Survey on T-Way Test Case Generation Strategies Based on Optimization Algorithms
Published 2014“…This paper presents an orchestrated survey of the existing OpA t-way strategies as Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Algorithm (ACA), Particle Swarm Optimization based strategy (PSTG), and Harmony Search Strategy (HSS). …”
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Book Chapter -
12
A swarm intelligent approach for multi-objective optimization of compact heat exchangers
Published 2023Article -
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A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem
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14
Harmony search-based robust optimal controller with prior defined structure
Published 2013“…For further assessment, the proposed design strategy is then employed to design a control law for an electrical DC drive velocity controller used as a benchmark problem for the recent PSO-based and genetic algorithm optimization (GAO)-based robust controllers. …”
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15
Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…Two main aspects are used to classify the evolutionary algorithm variants: population-based and evolutionary strategies (variation and replacement). …”
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16
Iteration strategy and ts effect towards the performance of population based metaheuristics
Published 2020“…Three parent algorithms, namely, particle swarm optimization (PSO), gravitational search algorithm (GSA), and simulated Kalman filter (SKF) are used in this work to find a general pattern of the effect of iteration strategy towards the performance of population-based algorithms. …”
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17
Fuzzy adaptive teaching learning-based optimization strategy for pairwise testing
Published 2017“…Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm is an improved form of Teaching Learning-based Optimization (TLBO) algorithm. …”
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18
Opposition-based manta ray foraging algorithm for global optimization and its application to optimize nonlinear type-2 fuzzy logic control
Published 2024“…The proposed opposition-based MRFO (OMRFO) algorithms are applied to optimize the IT2FLC control design for a laboratory-scaled inverted pendulum system. …”
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19
Hybrid Migrating Birds Optimization Strategy for t-way Test Suite Generation
Published 2019“…This paper presents the implementation of meta-heuristic search algorithms that are Migrating Birds Optimization (MBO) algorithm and Genetic Algorithm (GA) hybrid to a t-way test data generation strategy. …”
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20
Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems
Published 2022“…This study is aimed to formulate an optimization-based algorithm with simulation tool to reduce the throughput time of complex RMS, which can comply with complex product allocations and flexible routings of the system. …”
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