In this paper, a fuzzy multiobjective mathematical programming model for operational transport planning in a supply chain is presented. The objectives of the proposed model are the minimization of the number of used trucks and the total inventory level, by considering vehicle capacities as a...

In this work, we propose an integer linear programming model for production scheduling of a group of finished products with independent demand. The model for the master production scheduling (MPS) is designed by considering production and inventory costs, as well as the productive process...

We propose a new methodology for structural estimation of dynamic discrete choice models. We combine the Dynamic Programming (DP) solution algorithm with the Bayesian Markov Chain Monte Carlo algorithm into a single algorithm that solves the DP problem and estimates the parameters...

Dynamic discrete choice (DDC) models are not identified nonparametrically, but the non-identification of models does not necessarily imply the nonidentification of counterfactuals. We derive novel results for the identification of counterfactuals in DDC models, such as non-additive changes in...

In this work, we propose an integer linear programming model for production scheduling of a group of finished products with independent demand. The model for the master production scheduling (MPS) is designed by considering production and inventory costs, as well as the productive process...

Dynamic discrete choice (DDC) models are not identified nonparametrically, but the non-identification of models does not necessarily imply the nonidentification of counterfactuals. We derive novel results for the identification of counterfactuals in DDC models, such as non-additive changes in...

We propose a new methodology for structural estimation of dynamic discrete choice models. We combine the Dynamic Programming (DP) solution algorithm with the Bayesian Markov Chain Monte Carlo algorithm into a single algorithm that solves the DP problem and estimates the parameters...