Search Results - (( using linear problem algorithm ) OR ( java application clustering algorithm ))
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Thesis -
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A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…The prototypes will be developed using JAVA language united with a MySQL database. Core functionality of the simulator are job generation, volunteer generation, simulating algorithms, generating graphical charts and generating reports. …”
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Final Year Project -
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Comparison Between Linear Programming And Integer Linear Programming: A Review
Published 2018“…Three criteria were used to evaluate the characteristics: time complexity, problem size and computational time. …”
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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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Genetic algorithm techniques for the design of nonlinear microwave circuits
Published 2004“…By using Sample Balance's differential of current linear and nonlinear equation as an objective function, a Genetic Algorithm routine then been constructed. …”
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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…Later, this algorithm was used to solve bi-objective Production Planning (PP) and Scheduling Problem (Sch.P). …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Conference or Workshop Item -
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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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Hybrid evolutionary optimization algorithms: A case study in manufacturing industry
Published 2014“…This membership function is applied for its useful performance through industrial production problems by employing hybrid evolutionary optimization algorithms. …”
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Book -
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A web-based implementation of k-means algorithms
Published 2022“…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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Final Year Project / Dissertation / Thesis -
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Development of optimization Alghorithm for uncertain non-linear dynamical system
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…The first proposed approach is a multi-objective fuzzy linear programming optimization (MFLP) algorithm to solve the MOOPF problem. …”
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Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance
Published 2021“…Linear programming (LP) is a mathematical modelling that formulate a problem into three components which are decision variables, objective function and constraints. …”
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Path planning algorithm for a car like robot based on MILP method
Published 2013“…It is shown that this problem can be rewritten as a linear program with mixed integer / linear constraints that account for the collision avoidance. …”
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Classification for large number of variables with two imbalanced groups
Published 2020“…Several approaches have been devoted to study such problems using linear and non-linear classification rules, but limited to group imbalance rather than the combination of both problems. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…The performance of the proposed algorithm is also compared to the model developed using the orthogonal least squares (OLS) algorithm. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…The performance of the proposed algorithm is also compared to the model developed using the orthogonal least squares (OLS) algorithm. …”
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