http://cepac.cheme.cmu.edu/pasilectures/sahinidis/NVSpaperthree.pdf

Optimization under uncertainty: state-of-the-art and opportunities

http://cepac.cheme.cmu.edu/pasilectures/pinto/revpaper-NS2.pdf

Pharmaceutical supply chains: key issues and strategies for optimisation

http://egon.cheme.cmu.edu/Papers/FOCAPDK10451_C005.pdf?origin=publication_detail

Scope for the application of mathematical programming techniques in the synthesis and planning of sustainable processes

A two-stage stochastic programming model for the optimal design of distributed energy systems

This paper provides an overview of the key contributions within the planning and scheduling communities with specific emphasis on uncertainty analysis. As opposed to focusing in one particular industry, several independent sectors have been reviewed in order to find commonalities and potential avenues for future interdisciplinary collaborations. The objectives and physical constraints present within the planning and scheduling problems may vary greatly from one sector to another; however, all problems share the common attribute of needing to model parameter uncertainty in an explicit manner. It will be demonstrated through the literature review that two-stage stochastic programming, parametric programming, fuzzy programming, chance constraint programming, robust optimization techniques, conditional value-at-risk, and other risk mitigation procedures have found widespread application within all of the analyzed sectors. This review is the first work which attempts to provide a comprehensive description of t...

Planning and Scheduling under Uncertainty: A Review Across Multiple Sectors

A disaggregation algorithm for the optimization of stochastic planning models

"In order to solve the production planning problem given in 'Part I', a successive disaggregation algorithm is developed based on extensive sensitivity analysis for guiding the decisions on how to repartition the aggregate probability space. The partitioning algorithm is guaranteed to converge to the exact solution in a finite number of iterations, and has a highly parallel decomposition and computer implementation. Example problems are presented to demonstrate the solution technique. Results are compared with the alternative solution methods, variants of Benders decomposition schemes tailored to the dynamic staircase LP structure."

R. L. Clay

Papers

A disaggregation algorithm for the optimization of stochastic planning models

Optimization of stochastic planning models.