In classical newsvendor games, vendors collaborate to serve their aggregate demand whose joint distribution is assumed known with certainty. We investigate a new class of newsvendor games with ambiguity in the joint demand distributions, which is represented by a Fréchet class of distributions with some, possibly overlapping, marginal information. To model this new class of games, we use ideas from distributionally robust optimization to handle distributional ambiguity and study the robust newsvendor games. We provide conditions for the existence of core solutions of these games using the structural analysis of the worst-case joint demand distributions of the corresponding distributionally robust newsvendor optimization problem
We introduce a new distributionally robust optimization model to address a two-period, multi-item jo...
The traditional decision making framework for the newsvendor model is to assume a distribution of th...
We develop several distributionally robust equilibrium models, following the recent research surge o...
In classical newsvendor games, vendors collaborate to serve their aggregate demand whose joint distr...
In classical newsvendor games, vendors collaborate to serve their aggregate demand whose joint distr...
We use distributionally robust stochastic programs (DRSP) to model a general class of newsvendor pro...
This dissertation investigates robust optimization for use in demand forecasting. Techniques of robu...
This study considers a supply chain that consists of n retailers, each of them facing a newsvendor p...
We generalize analysis of competition among newsvendors to a setting in which competitors possess as...
This study considers a supply chain that consists of n retailers, each of them facing a newsvendor p...
We report preliminary results on stochastic optimization with limited distributional information. La...
We present a risk-averse multi-dimensional newsvendor model for a class of products whose demands ar...
We study a situation with n retailers, each of them facing a news-vendor problem, i.e., selling to c...
We present a risk-averse multi-dimensional newsvendor model for a class of products whose demands ar...
We generalize analysis of competition among newsvendors to a setting in which competitors possess as...
We introduce a new distributionally robust optimization model to address a two-period, multi-item jo...
The traditional decision making framework for the newsvendor model is to assume a distribution of th...
We develop several distributionally robust equilibrium models, following the recent research surge o...
In classical newsvendor games, vendors collaborate to serve their aggregate demand whose joint distr...
In classical newsvendor games, vendors collaborate to serve their aggregate demand whose joint distr...
We use distributionally robust stochastic programs (DRSP) to model a general class of newsvendor pro...
This dissertation investigates robust optimization for use in demand forecasting. Techniques of robu...
This study considers a supply chain that consists of n retailers, each of them facing a newsvendor p...
We generalize analysis of competition among newsvendors to a setting in which competitors possess as...
This study considers a supply chain that consists of n retailers, each of them facing a newsvendor p...
We report preliminary results on stochastic optimization with limited distributional information. La...
We present a risk-averse multi-dimensional newsvendor model for a class of products whose demands ar...
We study a situation with n retailers, each of them facing a news-vendor problem, i.e., selling to c...
We present a risk-averse multi-dimensional newsvendor model for a class of products whose demands ar...
We generalize analysis of competition among newsvendors to a setting in which competitors possess as...
We introduce a new distributionally robust optimization model to address a two-period, multi-item jo...
The traditional decision making framework for the newsvendor model is to assume a distribution of th...
We develop several distributionally robust equilibrium models, following the recent research surge o...