Search Results - (( integer implementation case algorithm ) OR ( java global optimization algorithm ))
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Case Slicing Technique for Feature Selection
Published 2004“…Case Slicing Technique (CST) helps in identifying the subset of features used in computing the similarity measures needed by classification algorithms. …”
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Thesis -
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Monograph -
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Development of symbolic algorithms for certain algebraic processes
Published 2007“…In the case of dense Legendre basis polynomials with a big GCD solution, the modular algorithm is significantly superior to the nonmodular algorithms in higher degree polynomials. …”
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Monograph -
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Development of symbolic algorithms for certain algebraic processes
Published 2007“…In the case of dense Legendre basis polynomials with a big GCD solution, the modular algorithm is significantly superior to the nonmodular algorithms in higher degree polynomials. …”
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Monograph -
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Reverse logistics network optimizing by genetic algorithm: a case study of automotive wiring harnesses
Published 2014“…With regards to the complexity of the reverse logistics network, traditional method cannot be implemented for solving them. Thus, an evolutionary algorithm based genetic algorithm (GA) is applied as a solution methodology to solve mixed integer linear programming model and find the optimum solution. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. …”
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Resource management in grid computing using ant colony optimization
Published 2011“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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Monograph -
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems
Published 2018“…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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Visdom: Smart guide robot for visually impaired people
Published 2025“…Key features include the SMAC Hybrid A* algorithm for global path planning, the Regulated Pure Pursuit Controller for local trajectory execution and dynamic obstacle avoidance, and gmapping for SLAM functionality. …”
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Final Year Project / Dissertation / Thesis -
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A study on the significance of backlash width values to the performance of the MIQP-based design of MPC
Published 2005“…Simulation results via an industrial Fluidized Catalytic Cracking Unit (FCCU) case study are presented to show the significance of precise estimation of the backlash width in ensuring successful implementation of the MIQP-based design of MPC.…”
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Conference or Workshop Item -
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Propositional satisfiability method in rough classification modeling for data mining
Published 2002“…Two models, Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) to represent the minimal reduct computation problem were proposed. …”
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Thesis -
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Energy-aware task scheduling for streaming applications on NoC-based MPSoCs
Published 2024“…Our approach is supported by a set of novel techniques, which include constructing an initial schedule based on a list scheduling where the priority of each task is its approximate successor-tree-consistent deadline such that the workload across all the processors is balanced, a retiming heuristic to transform intraperiod dependencies into inter-period dependencies for enhancing parallelism, assigning an optimal discrete frequency for each task and each message using a Non-Linear Programming (NLP)-based algorithm and an Integer-Linear Programming (ILP)-based algorithm, and an incremental approach to reduce the memory usage of the retimed schedule in case of memory size violations. …”
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