Search results for "Adaptive"
showing 10 items of 792 documents
Explicit Recursive and Adaptive Filtering in Reproducing Kernel Hilbert Spaces
2014
This brief presents a methodology to develop recursive filters in reproducing kernel Hilbert spaces. Unlike previous approaches that exploit the kernel trick on filtered and then mapped samples, we explicitly define the model recursivity in the Hilbert space. For that, we exploit some properties of functional analysis and recursive computation of dot products without the need of preimaging or a training dataset. We illustrate the feasibility of the methodology in the particular case of the $\gamma$ -filter, which is an infinite impulse response filter with controlled stability and memory depth. Different algorithmic formulations emerge from the signal model. Experiments in chaotic and elect…
A Hybrid Strategic Oscillation with Path Relinking Algorithm for the Multiobjective k-Balanced Center Location Problem
2021
This paper presents a hybridization of Strategic Oscillation with Path Relinking to provide a set of high-quality nondominated solutions for the Multiobjective k-Balanced Center Location problem. The considered location problem seeks to locate k out of m facilities in order to serve n demand points, minimizing the maximum distance between any demand point and its closest facility while balancing the workload among the facilities. An extensive computational experimentation is carried out to compare the performance of our proposal, including the best method found in the state-of-the-art as well as traditional multiobjective evolutionary algorithms.
GRASP and Path Relinking for the Two-Dimensional Two-Stage Cutting-Stock Problem
2007
We develop a greedy randomized adaptive search procedure (GRASP) for the constrained two-dimensional two-stage cutting-stock problem. This is a special cutting problem in which the cut is performed in two phases. In the first phase, the stock rectangle is slit down its width into different vertical strips and in the second phase, each of these strips is processed to obtain the final pieces. We propose two different algorithms based on GRASP methodology. One is “piece-oriented” while the other is “strip-oriented.” Both procedures are fast and provide solutions of different structures to this cutting problem. We also propose a path-relinking algorithm, which operates on a set of elite soluti…
Implementing some Evolutionary Computing Methods for Determining the Optimal Parameters in the Turning Process
2015
In this paper, we comparatively present two heuristics search methods – Simulated Annealing and Weighted Sum Genetic Algorithm, in order to find optimal cutting parameters in turning operation. We consider five different constraints aiming to achieve minimum total cost of machining. We developed a customizable software application in Microsoft Visual Studio with C# source code, flexible and extensible that implements the optimization methods. The experiments are based on real data gathered from S.C. “Compa” S.A Sibiu, a company that manufactures automotive components and targets improving of product quality and reducing cost and production time. The obtained results show that, although the …
Reactive GRASP for the strip-packing problem
2008
This paper presents a greedy randomized adaptive search procedure (GRASP) for the strip packing problem, which is the problem of placing a set of rectangular pieces into a strip of a given width and infinite height so as to minimize the required height. We investigate several strategies for the constructive and improvement phases and several choices for critical search parameters. We perform extensive computational experiments with well-known instances which have been previously reported, first to select the best alternatives and then to compare the efficiency of our algorithm with other procedures. The results show that the GRASP algorithm outperforms recently reported metaheuristics.
Adaptive memory programming for constrained global optimization
2010
The problem of finding a global optimum of a constrained multimodal function has been the subject of intensive study in recent years. Several effective global optimization algorithms for constrained problems have been developed; among them, the multi-start procedures discussed in Ugray et al. [1] are the most effective. We present some new multi-start methods based on the framework of adaptive memory programming (AMP), which involve memory structures that are superimposed on a local optimizer. Computational comparisons involving widely used gradient-based local solvers, such as Conopt and OQNLP, are performed on a testbed of 41 problems that have been used to calibrate the performance of su…
Cross-entropy-based adaptive optimization of simulation parameters for Markovian-driven service systems
2005
Abstract Markov fluid models represent a general description of the process of service request arrivals to service systems. The solution of performance analysis problems incorporating them often calls for a simulation approach, for which a reference methodology is Importance Sampling. However, in this case the appropriate choice of the biasing conditions is a problem in itself. In this paper an iterative method based on the cross-entropy is proposed for this choice. The equations are given that allow to derive the biasing conditions from the simulation itself. The application of the proposed method to three different sample cases, referring to one transient scenario (finite time horizon and…
GRASP and path relinking for the matrix bandwidth minimization
2004
In this article we develop a greedy randomized adaptive search procedure (GRASP) for the problem of reducing the bandwidth of a matrix. This problem consists of finding a permutation of the rows and columns of a given matrix, which keeps the nonzero elements in a band that is as close as possible to the main diagonal. The proposed method may be coupled with a Path Relinking strategy to search for improved outcomes. Empirical results indicate that the proposed GRASP implementation compares favourably to classical heuristics. GRASP with Path Relinking is also found to be competitive with a recently published tabu search algorithm that is considered one of the best currently available for band…
Greedy randomized adaptive search procedure with exterior path relinking for differential dispersion minimization
2015
We propose several new hybrid heuristics for the differential dispersion problem, the best of which consists of a GRASP with sampled greedy construction with variable neighborhood search for local improvement. The heuristic maintains an elite set of high-quality solutions throughout the search. After a fixed number of GRASP iterations, exterior path relinking is applied between all pairs of elite set solutions and the best solution found is returned. Exterior path relinking, or path separation, a variant of the more common interior path relinking, is first applied in this paper. In interior path relinking, paths in the neighborhood solution space connecting good solutions are explored betwe…
Error Estimates and Automatic Adaptive Mesh Refinement for the Metal Forming FEM Analysis
1988
The Authors propose a new technique which enables a estimation of the error inherent with the FEM analysis of metal forming processes. The aim is to evaluate the zones where the error is higher in order to proceed to a refinement of the mesh in such zones, and to obtain a smaller value of the global error. Moreover, to simplify the analyst work in the progressive refinement of the mesh, it has been prepared a software able to read the drawing created by a CAD program and to generate, automatically, all the geometrical and topological data necessary to perform the analysis on Personal Computer. The automatic renumbering of the elements in the refined mesh has been performed with the aim to r…