We consider a class of stochastic processing networks. Assume that the networks satisfy a complete resource pooling condition. We prove that each maximum pressure policy asymptotically minimizes the workload process in a stochastic processing network in heavy traffic. We also show that, under each quadratic holding cost structure, there is a maximum pressure policy that asymptotically minimizes...

In this research, we address the application of uncertaintyprogramming to design a multi-site, multi-product, multi-period,closed-loop supply chain (CLSC) network. In order to make theresults of this article more realistic, a CLSC for a case study inthe iron and steel industry has been explored. The presentedsupply chain covers three objective functions: maximization ofprofit, minimization of n...

We introduce a stochastic model for complex networks possessing three qualitative features: power-law degree distributions, local clustering, and slowly growing diameter. The model is mathematically natural, permits a wide variety of explicit calculations, has the desired three qualitative features, and fits the complete range of degree scaling exponents and clustering parameters.

This is a chapter of the forthcoming Oxford Handbook on the Economics of Networks.

We consider survivable network design problems under a two-stage stochastic model with recourse and finitely many scenarios (SSNDP). We propose two new cut-based formulations for SSNDP based on orientation properties and show that they are stronger than the undirected cut-based model. We use a two-stage branch&cut algorithm for solving the decomposed model to provable optimality. In order to ac...

Expected utility and risk analysis for stochastic influence networks requires accounting for the complex interconnections between agents as well as between agents and stochastic phenomena. Conditional game theory provides a framework within which to study expected utility and risk for such networks. Key features of this approach are a) mechanism for modulating individual preferences in response...

BACKGROUND Signaling networks are designed to sense an environmental stimulus and adapt to it. We propose and study a minimal model of signaling network that can sense and respond to external stimuli of varying strength in an adaptive manner. The structure of this minimal network is derived based on some simple assumptions on its differential response to external stimuli. METHODOLOGY We emplo...

Linear regression is the use of linear functions to model relationship between a dependent variable and one or more independent variables. models have been widely used in various fields such as finance, industry, medicine. To address problem that traditional difficult handle uncertain data, we propose granule-based elastic network model. First construct granules granular vectors by granulation ...