Search results for "generalization"
showing 10 items of 250 documents
Optimum plastic design for multiple sets of loads
1974
We study optimum plastic design of structures made up, or conceived as assemblies of finite elements, each having an elemental piece-wise linear rigid-plastic behaviour. Since cost function linearly dependent on design variables are considered, optimization problems in linear programming are encountered. Allowance is made for design dependent mass forces, and for some technological constraints. The design growing process is studied in the case of various sets of alternative applied loads, and the optimality conditions are written in a proper geometrical form which leads to a generalization of the concept of Foulkes mechanism.
Partially Renewable Resources
2014
In recent years, in the field of project scheduling the concept of partially renewable resources has been introduced. Theoretically, it is a generalization of both renewable and non-renewable resources. From an applied point of view, partially renewable resources allow us to model a large variety of situations that do not fit into classical models, but can be found in real problems in timetabling and labor scheduling. In this chapter we define this type of resource, describe an integer linear formulation and present some examples of conditions appearing in real problems which can be modeled using partially renewable resources. Then we introduce some preprocessing procedures to identify infe…
Large multiple neighborhood search for the clustered vehicle-routing problem
2018
Abstract The clustered vehicle-routing problem is a variant of the classical capacitated vehicle-routing problem in which customers are partitioned into clusters, and it is assumed that each cluster must have been served completely before the next cluster is served. This decomposes the problem into three subproblems, i.e., the assignment of clusters to routes, the routing inside each cluster, and the sequencing of the clusters in the routes. The second task requires the solution of several Hamiltonian path problems, one for each possibility to route through the cluster. We pre-compute the Hamiltonian paths for every pair of customers of each cluster. We present a large multiple neighborhood…
Necessary conditions for extremality and separation theorems with applications to multiobjective optimization
1998
The aim of this paper is to give necessary conditions for extremality in terms of an abstract subdifferential and to obtain general separation theorems including both finite and infinite classical separation theorems. This approach, which is mainly based on Ekeland's variational principle and the concept of locally weak-star compact cones, can be considered as a generalization f the notions of optima in problems of scalar or vector optimization with and without constraints. The results obtained are applied to derive new necessary optimality conditions for Pareto local minimum and weak Pareto minimum of nonsmooth multlobjectivep rogramming problems.
Asplund Operators on Locally Convex Spaces
2000
We study the relationship between the local Radon-Nikodým property, introduced by Defant [4] as a generalization of the Radon-Nikodým property to duals of locally convex spaces, and the Asplund operators, introduced by Robertson [7]. We also give a characterization of Asplund symmetric tensor products of Banach spaces in terms of Asplund maps.
Some Examples for Solving Clinical Problems Using Neural Networks
2001
In this paper neural networks are presented for solving some pharmaceutical problems. We have predicted and prevented patients with potential risk of post-Chemotherapy Emesis and potentially intoxicated patients treated with Digoxin. Neural networks have been also used for predicting Cyclosporine A concentration and Erythropoietin concentrations. Several neural networks (multilayer perceptron for classification tasks and Elman and FIR networks for prediction) and classical methods have been used. Results show how neural networks are very suitable tools for classification and prediction tasks, outperforming the classical methods. In a neural approach it is not strictly necessary to assume a …
Complex fractional moments for the characterization of the probabilistic response of non-linear systems subjected to white noises
2019
In this chapter the solution of Fokker-Planck-Kolmogorov type equations is pursued with the aid of Complex Fractional Moments (CFMs). These quantities are the generalization of the well-known integer-order moments and are obtained as Mellin transform of the Probability Density Function (PDF). From this point of view, the PDF can be seen as inverse Mellin transform of the CFMs, and it can be obtained through a limited number of CFMs. These CFMs’ capability allows to solve the Fokker-Planck-Kolmogorov equation governing the evolutionary PDF of non-linear systems forced by white noise with an elegant and efficient strategy. The main difference between this new approach and the other one based …
Poisson white noise parametric input and response by using complex fractional moments
2014
Abstract In this paper the solution of the generalization of the Kolmogorov–Feller equation to the case of parametric input is treated. The solution is obtained by using complex Mellin transform and complex fractional moments. Applying an invertible nonlinear transformation, it is possible to convert the original system into an artificial one driven by an external Poisson white noise process. Then, the problem of finding the evolution of the probability density function (PDF) for nonlinear systems driven by parametric non-normal white noise process may be addressed in determining the PDF evolution of a corresponding artificial system with external type of loading.
Motivic matching strategies for automated pattern extraction
2007
This article proposes an approach to the problem of automated extraction of motivic patterns in monodies. Different musical dimensions, restricted in current approaches to the most prominent melodic and rhythmic features at the surface level, are defined. The proposed strategy of detection of repeated patterns consists of an exact matching of the successive parameters forming the motives. We suggest a generalization of the multiple-viewpoint approach that allows a variability of the types of parameters (melodic, rhythmic, etc.) defining each successive extension of these motives. This enables us to take into account a more general class of motives, called heterogeneous motives, which inclu…
Strong solutions to a parabolic equation with linear growth with respect to the gradient variable
2018
Abstract In this paper we prove existence and uniqueness of strong solutions to the homogeneous Neumann problem associated to a parabolic equation with linear growth with respect to the gradient variable. This equation is a generalization of the time-dependent minimal surface equation. Existence and regularity in time of the solution is proved by means of a suitable pseudoparabolic relaxed approximation of the equation and a passage to the limit.