Search results for " optimization"
showing 10 items of 2367 documents
On Fixed Point (Trial) Methods for Free Boundary Problems
1992
In this note we consider the trial methods for solving steady state free boundary problems. For two test examples (electrochemical machining and continuous casting) we discuss the convergence of a fixed point method. Moreover, using the techniques of shape optimization we introduce a modification of the method, which gives us superlinear convergence rate. This is also confirmed numerically.
Packing a trunk - Now with a twist!
2005
In an industry project with a German car manufacturer we are faced with the challenge of placing a maximum number of uniform rigid rectangular boxes in the interior of a car trunk. The problem is of practical importance due to a European industry norm which requires car manufacturers to state the trunk volume according to this measure. No really satisfactory automated solution for this problem has been known in the past. In spite of its NP hardness, combinatorial optimization techniques, which consider only grid-aligned placements, produce solutions which are very close to the one achievable by a human expert in several hours of tedious work. The remaining gap is mostly due to the constrain…
Combinatorial Optimization for Artificial Intelligence Enabled Mobile Network Automation
2021
This chapter discusses combinatorial optimization techniques for enabling intelligent automation in mobile networks. A number of discrete optimization problems pertinent to mobile network automation can be solved effectively using artificial intelligence based combinatorial optimization approaches such as heuristics and metaheuristics. Relevant use-cases include both initial parameter assignment during network roll-out, and continuous optimization of configuration management parameters during network operation and maintenance. We discuss mobile network automation use-cases and motivation for using different heuristics and metaheuristics in designing network optimization algorithms. To this …
An Adaptive Metamodel-Based Optimization Approach for Vehicle Suspension System Design
2014
Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2014/965157 The performance index of a suspension system is a function of the maximum and minimum values over the parameter interval. Thus metamodel-based techniques can be used for designing suspension system hardpoints locations. In this study, an adaptive metamodel-based optimization approach is used to find the proper locations of the hardpoints, with the objectives considering the kinematic performance of the suspension. The adaptive optimization method helps to find the optimum locations of the hardpoints efficiently as it may be unachie…
Partial Discharges analysis and parameters identification by continuous Ant Colony Optimization
2008
The technique of ant colony optimization has been employed in this paper to efficiently deal with the problem of parameters identification in partial discharge, PD, analysis. The latter is a continuous optimization problem. From the technical point of view the identification of these parameters allows the modeling of the phenomenon of Partial Discharges in dielectrics. In this way it is possible the early diagnosis of defects in Medium Voltage cable lines and components and thus it is possible to prevent possible outages and service interruptions. Analytically, the problem consists of finding the Weibull parameters of the Pulse Amplitude Distribution (PAD) distributions allowing the identif…
An evolutionary method for complex-process optimization
2010
10 páginas, 7 figuras, 7 tablas
Black box scatter search for general classes of binary optimization problems
2010
The purpose of this paper is to apply the scatter search methodology to general classes of binary problems. We focus on optimization problems for which the solutions are represented as binary vectors and that may or may not include constraints. Binary problems arise in a variety of settings, including engineering design and statistical mechanics (e.g., the spin glass problem). A distinction is made between two sets of general constraint types that are handled directly by the solver and other constraints that are addressed via penalty functions. In both cases, however, the heuristic treats the objective function evaluation as a black box. We perform computational experiments with four well-k…
SSPMO: A Scatter Tabu Search Procedure for Non-Linear Multiobjective Optimization
2007
We describe the development and testing of a metaheuristic procedure, based on the scatter-search methodology, for the problem of approximating the efficient frontier of nonlinear multiobjective optimization problems with continuous variables. Recent applications of scatter search have shown its merit as a global optimization technique for single-objective problems. However, the application of scatter search to multiobjective optimization problems has not been fully explored in the literature. We test the proposed procedure on a suite of problems that have been used extensively in multiobjective optimization. Additional tests are performed on instances that are an extension of those consid…
Memetic Algorithms in Continuous Optimization
2012
Intuitively, a set is considered to be discrete if it is composed of isolated elements, whereas it is considered to be continuous if it is composed of infinite and contiguous elements and does not contain “holes”.
Disturbed Exploitation compact Differential Evolution for Limited Memory Optimization Problems
2011
This paper proposes a novel and unconventional Memetic Computing approach for solving continuous optimization problems characterized by memory limitations. The proposed algorithm, unlike employing an explorative evolutionary framework and a set of local search algorithms, employs multiple exploitative search within the main framework and performs a multiple step global search by means of a randomized perturbation of the virtual population corresponding to a periodical randomization of the search for the exploitative operators. The proposed Memetic Computing approach is based on a populationless (compact) evolutionary framework which, instead of processing a population of solutions, handles …