Search Results - (( using optimization method algorithm ) OR ( problem representation using algorithm ))
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…This thesis presents a new approach to optimize the performance of a dual beam optical scanning system in terms of its scanning combinations and speed, using Genetic Algorithm (GA). …”
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A review of crossover methods and problem representation of genetic algorithm in recent engineering applications
Published 2020“…This paper reviews crossover methods and problem representation, e.g. in the form of binary coded and real coded representation, used by researchers in order to solve engineering operations. …”
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Representation Of Rational Bézier Quadratics Using Genetic Algorithm, Differential Evolution And Particle Swarm Optimization
Published 2013“…Alternatively, artificial intelligence techniques are widely used for optimization problem with shorter computation time. …”
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…The evolutionary algorithm has been extensively used to solve a range of combinatorial optimization problems. …”
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Vehicle routing problem using genetic algorithm / Shamini Nagaratnam
Published 2006“…This dissertation studies and explores the potential of using Genetic Algorithms to find the shortest path in Vehicle Routing Problem. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems
Published 2016“…The rationale behind developing algorithms using real encoding of chromosome representations is the limitations of binary encoding. …”
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An Efficient Genetic Algorithm for Large Scale Vehicle Routing Problem Subject to Precedence Constraints
Published 2015“…Vehicle routing problem is difficult to solve using exact methods especially for large size instances due to computational expensive. …”
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Optimization of RFID network planning using MDB-FA method
Published 2017“…The generated data are utilized as an input representation to apply into firefly algorithm based on Density-Based Algorithm (DBSCAN) to find the optimal network solution. …”
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Dissimilarity algorithm on conceptual graphs to mine text outliers
Published 2009“…The graphical text representation method such as Conceptual Graphs (CGs) attempts to capture the structure and semantics of documents.As such, they are the preferred text representation approach for a wide range of problems namely in natural language processing, information retrieval and text mining.In a number of these applications, it is necessary to measure the dissimilarity (or similarity) between knowledge represented in the CGs.In this paper, we would like to present a dissimilarity algorithm to detect outliers from a collection of text represented with Conceptual Graph Interchange Format (CGIF).In order to avoid the NP-complete problem of graph matching algorithm, we introduce the use of a standard CG in the dissimilarity computation.We evaluate our method in the context of analyzing real world financial statements for identifying outlying performance indicators.For evaluation purposes, we compare the proposed dissimilarity function with a dice-coefficient similarity function used in a related previous work.Experimental results indicate that our method outperforms the existing method and correlates better to human judgements. …”
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Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling
Published 2022“…The experimentations of the proposed algorithm are conducted using existing benchmark instances and a published case study on an energy-efficient job-shop model. …”
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Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement
Published 2011“…The basic structure of FACTS devices and their configuration is described. A heuristic method known as genetic algorithm is used to seek the optimum location and setting of these controllers where there are some works related to this case using various techniques. …”
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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…Particularly, swmcan addresses multi-view data noise using the l1-norm and optimizes the objective function through a novel iterative reweighted method. …”
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A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem
Published 2009“…In this study, we propose an Optimised Crossover Genetic Algorithm (OCGA) for the problem. The objective is to find a schedule which minimises the maximum lateness of the jobs in the presence of the sequence independent family setup times.In brief, the proposed OCGA uses binary representation to encode the problem. …”
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah
Published 2022“…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. …”
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks
Published 2022“…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. …”
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An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines
Published 2020“…Metaheuristic algorithms are known to be excellent tools for solving optimization problems. …”
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Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences
Published 2024journal::journal article -
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More on completion time algorithms for intermediate storage tanks in multiproduct batch process scheduling using matrix representation
Published 2008“…In this work, new completion time algorithms for UIS and FIS transfer policies are proposed using matrix representation. …”
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Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin
Published 2013“…This intractability is one of the reasons why the problem has been so widely studied. The problem was initially tackled by “exact methods” such as the branch and bound method, which is based on the exhaustive enumeration of a restricted region of solutions containing exact optimal solutions. …”
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