467,401 research outputs found
Dynamic Matching Market Design
We introduce a simple benchmark model of dynamic matching in networked
markets, where agents arrive and depart stochastically and the network of
acceptable transactions among agents forms a random graph. We analyze our model
from three perspectives: waiting, optimization, and information. The main
insight of our analysis is that waiting to thicken the market can be
substantially more important than increasing the speed of transactions, and
this is quite robust to the presence of waiting costs. From an optimization
perspective, naive local algorithms, that choose the right time to match agents
but do not exploit global network structure, can perform very close to optimal
algorithms. From an information perspective, algorithms that employ even
partial information on agents' departure times perform substantially better
than those that lack such information. To elicit agents' departure times, we
design an incentive-compatible continuous-time dynamic mechanism without
transfers
Duality between Feature Selection and Data Clustering
The feature-selection problem is formulated from an information-theoretic
perspective. We show that the problem can be efficiently solved by an extension
of the recently proposed info-clustering paradigm. This reveals the fundamental
duality between feature selection and data clustering,which is a consequence of
the more general duality between the principal partition and the principal
lattice of partitions in combinatorial optimization
A Tractable Fault Detection and Isolation Approach for Nonlinear Systems with Probabilistic Performance
This article presents a novel perspective along with a scalable methodology
to design a fault detection and isolation (FDI) filter for high dimensional
nonlinear systems. Previous approaches on FDI problems are either confined to
linear systems or they are only applicable to low dimensional dynamics with
specific structures. In contrast, shifting attention from the system dynamics
to the disturbance inputs, we propose a relaxed design perspective to train a
linear residual generator given some statistical information about the
disturbance patterns. That is, we propose an optimization-based approach to
robustify the filter with respect to finitely many signatures of the
nonlinearity. We then invoke recent results in randomized optimization to
provide theoretical guarantees for the performance of the proposed filer.
Finally, motivated by a cyber-physical attack emanating from the
vulnerabilities introduced by the interaction between IT infrastructure and
power system, we deploy the developed theoretical results to detect such an
intrusion before the functionality of the power system is disrupted
On a New Type of Information Processing for Efficient Management of Complex Systems
It is a challenge to manage complex systems efficiently without confronting
NP-hard problems. To address the situation we suggest to use self-organization
processes of prime integer relations for information processing.
Self-organization processes of prime integer relations define correlation
structures of a complex system and can be equivalently represented by
transformations of two-dimensional geometrical patterns determining the
dynamics of the system and revealing its structural complexity. Computational
experiments raise the possibility of an optimality condition of complex systems
presenting the structural complexity of a system as a key to its optimization.
From this perspective the optimization of a system could be all about the
control of the structural complexity of the system to make it consistent with
the structural complexity of the problem. The experiments also indicate that
the performance of a complex system may behave as a concave function of the
structural complexity. Therefore, once the structural complexity could be
controlled as a single entity, the optimization of a complex system would be
potentially reduced to a one-dimensional concave optimization irrespective of
the number of variables involved its description. This might open a way to a
new type of information processing for efficient management of complex systems.Comment: 5 pages, 2 figures, to be presented at the International Conference
on Complex Systems, Boston, October 28 - November 2, 200
Measuring performance in healthcare
Hospitals invest in process management and process optimization from an organizational and patient perspective to increase efficiency and simultaneously the quality of their operations. Consequently, the use of process-oriented performance measurement systems gains importance. This study contributes to the development of a dashboard for the process of hip surgery using a case study design. We integrate strategic goals of hospital management and different stakeholders with the analysis of Business Process Management and Hospital Information Systems’ data. Process-oriented KPIs were integrated into the dashboard using a three-step approach. Dashboards enable healthcare organizations to put process-oriented performance measurement into practice
Distributed Model Predictive Control Using a Chain of Tubes
A new distributed MPC algorithm for the regulation of dynamically coupled
subsystems is presented in this paper. The current control action is computed
via two robust controllers working in a nested fashion. The inner controller
builds a nominal reference trajectory from a decentralized perspective. The
outer controller uses this information to take into account the effects of the
coupling and generate a distributed control action. The tube-based approach to
robustness is employed. A supplementary constraint is included in the outer
optimization problem to provide recursive feasibility of the overall controllerComment: Accepted for presentation at the UKACC CONTROL 2016 conference
(Belfast, UK
- …