Search Results - (( programming problem function algorithm ) OR ( its application optimization algorithm ))
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1
Particle swarm optimization for neural network learning enhancement
Published 2006“…Backpropagation (BP) algorithm is widely used to solve many real world problems by using the concept of Multilayer Perceptron (MLP). …”
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2
Optimal multiple distributed generation output through rank evolutionary particle swarm optimization
Published 2015“…However, the REPSO algorithm provided the lowest SD value in all problems. …”
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3
Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja
Published 2004“…This thesis also provides an explanation about the advantages. functions, characteristics. the degree of complexity in A • algorithm and its implementation in real-world application. …”
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4
Differential evolution for neural networks learning enhancement
Published 2008“…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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5
Network reconfiguration and control for loss reduction using genetic algorithm
Published 2010“…The proposed solution to this problem is based on a general combinatorial optimization algorithm known as Genetic Algorithm, and the load flow equations in distribution network. …”
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6
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…DE has effectively solved various global optimization problems, including benchmark functions. These problems have shown different challenging characteristics such as non-convexity, non-linearity, and/or multi-modality which became difficult for traditional non-linear programming to deal with. …”
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7
1D Multigrid Solver For Finite Element Method
Published 2022“…Next, the algorithm was modified by using a new Gauss-Seidel function. …”
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A hybrid optimization technique for solving economic emission load dispatch problems
Published 2023text::Final Year Project -
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Angle Based Protein Tertiary Structure Prediction Using Bees Optimization Algorithm
Published 2010“…In this project, angles based control with Bees Optimization search algorithm were adopted to search with guidance the protein conformational space in order to find the optimum solution. …”
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10
Energy management system for optimal operation of microgrid consisting of PV, fuel cell and battery / Shivashankar Sukumar
Published 2017“…In addition, a novel ‘mix-mode’ operating strategy is proposed to reduce the microgrid’s daily operating cost. The objective functions in the proposed strategies are solved using linear programming and mixed integer linear programming. …”
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11
Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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12
Optimal location and sizing of SVC using Particle Swarm Optimization technique
Published 2011“…This paper describes optimal location and sizing of static var compensator (SVC) based on Particle Swarm Optimization for minimization of transmission losses considering cost function. Particle Swarm Optimization (PSO) is population-based stochastic search algorithms approaches as the potential techniques to solving such a problem. …”
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Discrete-time system identification using genetic algorithm with single parent-based mating technique
Published 2024“…These practical applications underscore the versatility and effectiveness of the SPM technique in enhancing GA for SI, proving its utility across different fields such as engineering, finance, and healthcare. …”
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14
Search and rescue optimization for combined economic load and emission dispatch
Published 2024“…The Search and Rescue (SAR) optimization methodology is developed in this study to address the CEED problem, and the results gained are compared with the Evolutionary Programming and Flower Pollination Algorithm methods. …”
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15
Load margin expansion for sustainable power system operation
Published 2018“…The performance of the proposed techniques were comprehensive analyzed between two other familiar optimization methods known as original Bacterial Foraging Optimization (BFO) algorithm and Meta heuristic Evolutionary Programming (Meta-EP) for standard IEEE 57 bus system. …”
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Load margin expansion for sustainable power system operation
Published 2018“…The performance of the proposed techniques were comprehensive analyzed between two other familiar optimization methods known as original Bacterial Foraging Optimization (BFO) algorithm and Meta heuristic Evolutionary Programming (Meta-EP) for standard IEEE 57 bus system. …”
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Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian
Published 2009“…This optimal state estimate and corrected data base are then used by the security monitoring and operation and control functions of the center.Most state estimation programs in practical use are formulated as overdetermined systems (Pozrikidis, 2008) of nonlinear equations and solved as weighted least square problems (refer to section 2.1.1).This research involves finding the least squares solution of the power system state estimation problem, HTR-1HDx = HTR-1 [z - f (x)] (refer to section 2.3.1) and to develop a program to implement the said algorithm. …”
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18
Analytical Approach for Linear Programming Using Barrier and Penalty Function Methods
Published 2003“…None of these methods used Lagrangian function as a tool to solve the problem. This raises a question why are we not using this to solve the linear programming problems. …”
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19
Some metaheuristic algorithms for solving multiple cross-functional team selection problems
Published 2022“…We introduced a method that combines a compromise programming (CP) approach and metaheuristic algorithms, including the genetic algorithm (GA) and ant colony optimization (ACO), to solve the proposed optimization problem. …”
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20
On network flow problems with convex cost
Published 2004“…To address this problem, we derive the optimality conditions for minimising convex and differentiable cost functions, and devise an algorithm based on the primal-dual algorithm commonly used in linear programming. …”
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