Search Results - (( developing function _ algorithm ) OR ( its application optimization algorithm ))
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…Its optimality has inspired the development of a metaheuristic algorithm called Heuristic Kalman Algorithm (HKA) in 2009. …”
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A multi-objective Spiral Dynamic algorithm and its application for PD design
Published 2017“…In terms of its application in solving a real problem, both algorithms successfully optimize the PD and control the system very well. …”
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Convergence Analysis of the African Buffalo Optimization Algorithm
Published 2016“…The analysis of the convergence of Nature-inspired optimization algorithms is necessary to help researchers and practitioners understand the workings of the algorithms in the algorithms’ attempts at solutions. …”
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Development Of Artificial Bee Colony (Abc) Variants And Memetic Optimization Algorithms
Published 2017“…One of BIAs, artificial bee colony (ABC) optimization algorithm, has shown excellent performance in many applications compared to other optimization algorithms. …”
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New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…In the fourth phase, the newly developed algorithm undergoes testing on the formulated ROOPs and compared to several contemporary optimizer algorithms. …”
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Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid
Published 2012“…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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Monograph -
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A Novel Discrete Filled Function Algorithm in Solving Discrete Optimization Problems (S/O: 12408)
Published 2016“…Numerical results suggest that the proposed algorithm is efficient in solving large scale complex discrete optimization problems, thus could be extended into solving real life application mixed discrete optimization problem in the future…”
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Monograph -
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DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS
Published 2012“…The issue is not only to develop new algorithms, but also to evaluate them on an experimental computational grid, using synthetic and real workload traces, along with the other existing job scheduling algorithms. …”
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Non-dominated sorting manta ray foraging algorithm with an application to optimize PD control
Published 2022“…Meanwhile, CD is a strategy to preserve good distribution of solutions along the PF. This proposed algorithm is called NSMRFO. It is tested using several benchmark functions and its performance is compared to its parent by using statically analysis of hypervolume indicator. …”
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An Improved Spiral Dynamic Optimization Algorithm with Engineering Application
Published 2015“…This paper presents the development of an improved spiral dynamic optimization algorithm with application to nonparametric fuzzy logic modeling of a twin rotor system (TRS). …”
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Development of improved metaheuristic algorithms for modelling and control of a flexible manipulator system
Published 2019“…This project develops two variants of single-objective type optimization algorithm and two variants of multi-objective type optimization algorithm. …”
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Research Report -
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Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots
Published 2006“…A fitness function has been created from the preliminary experiment with optimized two conflicting objectives: (1) maximize the virtual Khepera robot's behavior for homing towards a RF signal source and (2) minimize the number of hidden neurons used in its ANNs controller by the utilization of Pareto-frontier Differential Evolutionary Multi-objective (POE) algorithm. …”
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An Optimized PID Parameters for LFC in Interconnected Power Systems Using MLSL Optimization Algorithm
Published 2016“…Integral Square Error (ISE) is considered as an objective function for both algorithms to determine its performance index value for the same interconnected power system. …”
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Optimization of multi-holes drilling toolpath using tiki-taka algorithm
Published 2024“…A computational experiment was conducted on 12 test problems across small, medium, and large problem categories using the TTA, then compared with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Crayfish Optimization Algorithm (COA), and Geometric Mean Optimizer (GMO). …”
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Particle swarm optimization for neural network learning enhancement
Published 2006“…Two programs have been developed; Particle Swarm Optimization Feedforward Neural Network (PSONN) and Genetic Algorithm Backpropagation Neural Network (GANN). …”
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Optimized processing of satellite signal via evolutionary search algorithm
Published 2000“…The PRSS algorithm is an adaptive search technique that can learn a high performance knowledge structure in reactive environments that provide information as an objective function. …”
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Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method
Published 2024“…It ensures that the obtained parameters reflect the true characteristics of the PV system, leading to more accurate and reliable results in various applications. The existing literature extensively explores the utilization of powerful Metaheuristic Algorithms (MAs) to address the complex constrained optimization problem in PV systems and achieve optimal solutions. …”
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