This paper reviews recent advances in the field of optimization under uncertainty via a
modern data lens, highlights key research challenges and promise of data-driven …

As supply chain risk management has transitioned from an emerging topic to a growing
research area, there is a need to classify different types of research and examine the …

Uncertainties are widespread in the optimization of process systems, such as uncertainties
in process technologies, prices, and customer demands. In this paper, we review the basic …

Supply-chain uncertainty is an issue with which every practising manager wrestles, deriving
from the increasing complexity of global supply networks. Taking a broad view of supply …

Supply risk or the likelihood of supply disruptions is emerging as a key challenge to supply
chain management. The ability to identify which supplier has greater potential of a disruption …

Many industries are facing big challenges to design supply chains in a way to maximize the
profit and meet the heightened expectations of the customer. This new era entirely relies on …

Rising populations put huge stresses on natural resources. Extraction and depletion of raw
materials and waste created throughout the supply chain of products have enormous …

The consideration of uncertainty in manufacturing systems supposes a great advance.
Models for production planning which do not recognize the uncertainty can be expected to …

In this paper, a mixed integer linear programming (MILP) formulation is developed for the
design and planning of supply chains with reverse flows while considering simultaneously …

This paper presents a review of mathematical programming models for supply chain
production and transport planning. The purpose of this review is to identify current and future …