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iterative optimization » objective optimization (Expand Search), storage optimization (Expand Search)
iterative optimization » objective optimization (Expand Search), storage optimization (Expand Search)
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Animal migration optimization algorithm: novel optimizer, analysis, and applications
Published 2024Subjects: “…Animal migration optimization…”
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Optimal selection of the forgetting matrix into an iterative learning control algorithm
Published 2005“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the optimal forgetting matrix and the learning gain matrix of a P-type iterative learning control (ILC) for linear discrete-time varying systems with arbitrary relative degree. …”
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Stochastic P-type/D-type iterative learning control algorithms
Published 2003“…This paper presents stochastic algorithms that compute optimal and sub-optimal learning gains for a P-type iterative learning control algorithm (ILC) for a class of discrete-time-varying linear systems. …”
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On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise
Published 2005“…Higher-Order Iterative Learning Control (HO-ILC) algorithms use past system control information from more than one past iterative cycle. …”
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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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A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems
Published 2024“…The ES algorithm begins with a random initial solution and uses an insertion mutation to optimize the solution. …”
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Particle swarm optimization algorithm: review and applications
Published 2024“…Particle swarm optimization (PSO) is a heuristic global optimization technique and an optimization algorithm that is swarm intelligence-based. …”
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Reliability and fault tolerance based topological optimization of computer networks - part II: iterative techniques
Published 2003“…We consider the use of three iterative techniques, namely tabu search, simulated annealing, and genetic algorithms, in solving the multiobjective topological optimization network design problem. …”
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Iterative Least Squares Functional Networks Classifier
Published 2007“…Both methodology and learning algorithm for this kind of computational intelligence classifier using the iterative least squares optimization criterion are derived. …”
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Iterative heuristics for multiobjective VLSI standard cellplacement
Published 2001“…We employ two iterative heuristics for the optimization of VLSI standard cell placement. …”
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General iterative heuristics for VLSI multiobjective partitioning
Published 2003“…In this paper, we engineer two iterative heuristics for the optimization of VLSI netlist bi-Partitioning. …”
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A new family of multi-step quasi-Newton algorithms for unconstrained optimization
Published 1999“…It concentrates on deriving a variable-metric family of minimum curvature algorithms for unconstrained optimization. The derivation is based on considering a rational model, with a certain tuning parameter, where the aim is to develop a general framework that encompasses all possible two-step minimum curvature algorithms generated by appropriate parameter choices. …”
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Genetic and heuristic algorithms for regrouping service sites. (c2000)
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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain
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Enhancement of SAR Speckle Denoising Using the Improved Iterative Filter
Published 2020“…When the improved iterative filtering process was initialized by the nonlocal mean filter, for few iterations, the filtering performances were improved. …”
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
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Designing Cellular Mobile Networks Using Non{Deterministic Iterative Heuristics
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Parallelization of Iterative Heuristic for Performance-Driven Low-Power VLSI Standard Cell Placement.
Published 2003“…The complexity involved in VLSI design and its sub-problems has always made them ideal application areas for non-deterministic iterative heuristics. However, the major drawback has been the large runtime involved in reaching acceptable solutions especially in the case of multi-objective optimization problems. …”
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