Editorial special issue on “Robust and stochastic optimization in production systems and supply chain management”

Abstract

Uncertainty, disruptions, and variability are main challenges of manufacturing systems and supply chains. The design and operation of such systems have to incorporate uncertainty about the future. Adaptability and flexibility are desirable features of such systems, as are robust designs and plans. Operations research methods support strategic and operational decisions in production and supply chains and the evaluation of different concepts. However, there exist several different uncertainty modelling approaches that make different assumptions about the knowledge on availability and estimation of the required distributions and parameter values for optimization. This specially contains applied contributions on uncertainty modelling and optimization in the fields of logistics, manufacturing, and supply chain management where robust and/or stochastic models are used to provide decision support. This special issue was inspired by focused topics of the APMOD conference 2012 held at the University of Paderborn. Several manuscripts presented at the conference were submitted in response to an open call for papers on the topic. The following 5 selected manuscripts present applications of stochastic programming and robust optimization of several different industries and fields of application. Alem andMorabito, “Risk-averse two-stage stochastic program in furniture plants” present a case application from the furniture industry and use two-stage mixed-integer programming formulations under different decision criteria taking risk into account.