performance of a supply chain highly depends on its suppliers and therefore, appropriate selection of them is of great importance. this paper presents an integrated model of an mcdm method and a mathematical programming in order to select suppliers and determine lot sizes in the supply chain. the proposed framework comprises two main sub-models; the qualitative sub-model seeks to evaluate the s...

We study in this paper the first-order behavior of value functions in parametric dynamic programming with linear constraints and nonconvex cost functions. By establishing an abstract result on the Fréchet subdifferential of value functions of parametric mathematical programming problems, some new formulas on the Fréchet subdifferential of value functions in parametric dynamic programming are ob...

The fields of machine learning and mathematical programming are increasingly intertwined. Optimization problems lie at the heart of most machine learning approaches. The Special Topic on Machine Learning and Large Scale Optimization examines this interplay. Machine learning researchers have embraced the advances in mathematical programming allowing new types of models to be pursued. The special...

We study in this paper the first-order behavior of value functions in parametric dynamic programming with linear constraints and nonconvex cost functions. By establishing an abstract result on the Fréchet subdifferential of value functions of parametric mathematical programming problems, some new formulas on the Fréchet subdifferential of value functions in parametric dynamic programming are ob...

This paper considers a bi-objective mathematical model for locations of landfills, transfer stations and material recovery facilities (MRFs) in order to serve the entire regions and simultaneously identify the capacities of landfills. This is a mixed-integer programming (MIP) model, whose objectives are to minimize the total cost and pollution simultaneously. To validate the model, a numerical ...