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We analyze the information preferences and information demand of such decision-makers, based on properties of their payoff functions. We restrict attention to “monotone decision problems,” whe...
Many economic decisions involve a binary choice - for example, when consumers decide to purchase a good or when rms decide to enter a new market. In such settings, agents' choices often depend on im...
It is shown that many system stability and robustness problems can be reduced to the question of when there is a quadratic Lyapunov function of a certain structure which establishes stability of dx/dt...
Recent results have shown that several H_2 and H_2-related problems can be formulated as convex programs with a finite number of variables. We present an interior point algorithm for the solution of t...
A number of problems in the analysis and design of control systems may be reformulated as the problem of minimizing the largest generalized eigenvalue of a pair of symmetric matrices which depend affi...
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 ...
We point out some connections between applications of semidefinite programming in control and in combinatorial optimization. In both fields semidefinite programs arise as convex relaxations of NP-hard...
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...
Geometric programming (GP) describes a type of optimization problem that has been known since the 1970s, but recently has attracted more attention for several reasons. The first is the development of ...
This paper considers moving horizon estimation (MHE) approach to solution of staged quadratic programming (QP) problems. Using an insight into the constrained solution structure for the growing horizo...
We present an alternating augmented Lagrangian method for convex optimization problems where the cost function is the sum of two terms, one that is separable in the variable blocks, and a second that ...
We consider the problem of minimizing a sum of non-convex functions over a compact domain, subject to linear inequality and equality constraints. We consider approximate solutions obtained by solving ...
Reinforcement learning (RL) is concerned with the identification of optimal controls in Markov decision processes (MDPs) where no explicit model of the transition probabilities is available. Many exis...
If the system is singular, MINRES-QLP computes the unique minimum-length solution (also known as the pseudoinverse solution), which generally eludes MINRES. In all cases, it overcomes a potential in...
Many negotiators have constituencies that must formally or informally approve an agreement. Traditionally, it is the responsibility of each negotiator to manage the internal conflicts and constituenci...

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