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61
An evolutionary algorithm for solving the geometrically constrained site layout problem
Published 2017“…The proposed algorithm is two-phases: an initialization phase that generates an initial population of layouts through a sequence of mutation operations, and a reproduction phase that evolve the layouts generated in phase one through a sequence of genetic operations aiming at finding an optimal layout. …”
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conferenceObject -
62
Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
Published 2024“…This work aims to enhance the performance of the K-means algorithm by introducing a novel method for selecting the initial centroids, thereby minimizing randomness and reducing the number of iterations needed to reach optimal results. …”
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63
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64
Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm
Published 2023“…Therefore, the combined objective case studies are examined as minimization and maximization criteria, thus increasing the efficiency of the proposed method. …”
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65
An Optimal Repeat Inspection Plan With Several Classifications
Published 2020“…A mathematical model that depicts the plan is developed. An algorithm is proposed for finding the optimal number of repeat inspections and the sequence of characteristics for inspection that minimizes expected total cost per accepted component. …”
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66
A distributed genetic algorithm for deterministic and stochastic labor scheduling problems
Published 1999“…In this paper we present a unified formulation for these three labor scheduling problems and introduce a distributed genetic algorithm (DGA) that solves each of them. Our distributed genetic algorithm operates in parallel on a network of message-passing workstations. …”
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68
Stochastic P-type/D-type iterative learning control algorithms
Published 2003“…The optimal algorithm is based on minimizing the trace of the input error covariance matrix. …”
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69
On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise
Published 2005“…This paper addresses the optimality of HO-ILC in the sense of minimizing the control error covariance matrix in the presence of measurement noise. …”
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conferenceObject -
70
A stochastic iterative learning control algorithm with application to an induction motor
Published 2004“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the learning gain matrix of a P-type ILC for linear discrete-time varying systems with arbitrary relative degree. …”
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71
Metaheuristic algorithm for testing web 2.0 applications. (c2012)
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masterThesis -
72
PERF solutions for distributed query optimization. (c1999)
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masterThesis -
73
On Indefinite Quadratic Optimization over the Intersection of Balls and Linear Constraints
Published 2022“…<p>In this paper, we study the minimization of an indefinite quadratic function over the intersection of balls and linear inequality constraints (QOBL). …”
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74
CFD Based Airfoil Shape Optimization for Aerodynamic Drag Reduction
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doctoralThesis -
75
Genetic Algorithm for Solving Site Layout Problem with Unequal-Size and Constrained Facilities
Published 2002“…In most problems considered where the total-objects-to-site-area ratio did not exceed 60%, the algorithm returned close to optimal solutions in a reasonable time.…”
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76
Optimality of first-order ILC among higher order ILC
Published 2006“…That is, an optimal HO-ILC does not add to the optimality of standard first-order ILC in the sense of minimizing the trace of the control error covariance matrix. …”
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77
Power-constrained system-on-a-chip test scheduling using a genetic algorithm
Published 2006“…This paper presents an efficient approach for the test scheduling problem of core-based systems based on a genetic algorithm. The method minimizes the overall test application time of a system-on-a-chip through efficient and compact test schedules. …”
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Optimization of Battery Electric Bus Charging under Varying Operating Conditions
Published 2020“…This paper proposes an optimization algorithm based on Dynamic Programming that minimizes the total BEB energy costs and battery replacement costs by optimally controlling the BEB daily charging power throughout the year, considering the varying operating conditions. …”
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80
A new minimum curvator multi-step method for unconstrained optimization
Published 1998“…Our derivation of the new algorithm is based on determining some value of the parameter that minimizes the curvature in some chosen metric. …”
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