Chance-constrained formulations in rolling horizon production planning: an experimental study

Abstract

Rolling horizon procedures, where an infinite horizon problem is approximated by the solution to a sequence of finite horizon problems, are common in production planning practice and research. However, these procedures also lead to frequent changes in planned release and production quantities, a phenomenon referred to as nervousness. We examine the performance of two chance-constrained production planning models developed for systems with stochastic demand in a rolling horizon environment, and find that these formulations significantly reduce planned release changes (nervousness) while also improving cost and service-level performance.