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61
A Modular Reconfigurable Architecture for Asymmetric and Symmetric-key Cryptographic Algorithms
Published 2007“…Preliminary results show throughput values equivalent to FPGA based implementations for most of the tested ciphers, and approaching ASIC based implementations. …”
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masterThesis -
62
Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem
Published 1999“…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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63
A Parallel Tabu Search Algorithm for Optimizing Multiobjective VLSI Placement
Published 2005“…A comparison of the obtained results is made with the results of a parallel genetic algorithm (GA) implementation.…”
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64
A parallel optimization algorithm for the maximum clique problem. (c2008)
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masterThesis -
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66
Efficient methods and techniques for the open-shop scheduling problem. (c2006)
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masterThesis -
67
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68
Integrating Genetic Algorithms, Tabu Search, And Simulated Annealing For The Unit Commitment Problem
Published 2020“…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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69
New Fast Arctangent Approximation Algorithm for Generic Real-Time Embedded Applications
Published 2019“…A new 2nd order rational approximation formula is introduced for the first time in this work and benchmarked against existing alternatives as it improves the new algorithm performance. The eZDSP-F28335 platform has been used for practical implementation and results validation of the proposed technique. …”
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70
Genetic Algorithm Control Strategy for Heat Pump System in Battery Electric Buses
Published 2020“…This study proposes a genetic algorithm-based control strategy that optimizes the coefficient of performance of the HP system to decrease its energy consumption and maximize the driving range. …”
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conferenceObject -
71
A new tabu search algorithm for the long-term hydro scheduling problem
Published 2002“…The algorithm is based on using the short-term memory of the tabu search (TS) approach to solve the nonlinear optimization problem in continuous variables of the LTHSP. …”
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Genetic Algorithm Analysis using the Graph Coloring Method for Solving the University Timetable Problem
Published 2018“…The GA method is implemented in java, and the improvement of the initial solution is exhibited by the results of the experiments based on the specified constraints and requirements.…”
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A Parallel Genetic Algorithm for the Open-Shop Scheduling Problem Using Deterministic and Random Moves
Published 2016“…The method is based on a novel implementation of genetic operators that combines the use of deterministic and random moves. …”
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Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm
Published 2024“…To avoid such issues and provide the optimal solution, there are some modifications are implemented into the internal structure of t‐LCA based on Weibull flight operator, mutation‐based approach, quasi‐opposite‐based learning and gorilla troops exploitation‐based mechanisms to enhance the overall strength of the algorithm to obtain the global solution. …”
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New Hardware Algorithms and Designs for Montgomery Modular Inverse Computation in Galois Fields GF(p) and GF(2n)
Published 2002“…We compare all scalable designs with fully parallel ones based on the same basic inversion algorithm. All scalable designs consumed less area and in general showed better performance than the fully parallel ones, which makes the scalable design a very efficient solution for computing the long precision Montgomery inverse.…”
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masterThesis -
80
Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network
Published 2024“…The proposed model was developed and implemented using MATLAB software. A Pareto front was derived from the MOGA by employing the T2FNN within the process, identifying fourteen optimal solutions.…”