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2017 IACMR Research Method Workshop     2017  IACMR Research Method  Workshop       font style='font-size:12px;'> 2017/1/10
You are cordially invited to apply for the IACMR Research Methods Workshop to be held from July 9-13, 2017, at Huazhong University of Science & Technology, Wuhan, China. The purposes of the workshop a...
Market situation and business environment of construction companies influence significantly decisions met by this group of entities. These decisions are reflected in financial statements, later on. Th...
We consider the problem of minimizing the largest generalized eigenvalue of a pair of symmetric matrices, each of which depends affinely on the decision variables. Although this problem may appear spe...
We describe a potential reduction method for convex optimization problems involving matrix inequalities. The method is based on the theory developed by Nesterov and Nemirovsky and generalizes Gonzaga ...
In this paper we present a path-following (homotopy) method for (locally) solving bilinear matrix inequality (BMI) problems in control. The method is to linearize the BMI using a first order perturbat...
Logistic regression with l1 regularization has been proposed as a promising method for feature selection in classification problems. In this paper we describe an efficient interior-point method for so...
In downlink beamforming in a multiple-input multiple-output (MIMO) wireless communication system, we design beamformers that minimize the power subject to guaranteeing given signal-to-interference noi...
An Efficient Method for Large-Scale Gate Sizing     Gate sizing  geometric programming (GP)       font style='font-size:12px;'> 2015/7/9
We consider the problem of choosing the gate sizes or scale factors in a combinational logic circuit in order to minimize the total area, subject to simple RC timing constraints, and a minimum allowed...
This article considers the problem of reconstructing cone-beam computed tomography (CBCT) images from a set of undersampled and potentially noisy projection measurements. The authors cast the reconstr...
A Splitting Method for Optimal Control     Splitting Method  Optimal Control       font style='font-size:12px;'> 2015/7/9
We apply an operator splitting technique to a generic linear-convex optimal control problem, which results in an algorithm that alternates between solving a quadratic control problem, for which there ...
We develop a simple operator splitting method for solving a primal conic optimization problem; we show that the iterates also solve the dual problem. The resulting algorithm is very simple to describe...
This paper is concerned with the use of simulation to compute the conditional expectations that arise in the method of conditional least squares. Our approach involves performing simulations at each p...
The regenerative method enjoys asymptotic properties that make it a highly desirable approach for steady-state simulation output analysis. It has been shown that virtually all discrete-event simulatio...
Constrained Monte Carlo and the Method of Control Variates     Constrained Monte Carlo  Method  Control Variates       font style='font-size:12px;'> 2015/7/8
A constrained Monte Carlo problem arises when one computes an expectation in the presence of a priori computable constraints on the expectations of quantities that are correlated with the estimand. Th...
Some New Perspectives on the Method of Control Variates     Some New Perspectives  Method  Control Variates       font style='font-size:12px;'> 2015/7/8
The method of control variates is one of the most widely used variance reduction techniques associated with Monte Carlo simulation. This paper studies the method of control variates from several diffe...

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