Mixed-Integer Programming Model and Tightening Methods for Scheduling in General Chemical Production Environments

Abstract

We develop a mixed-integer programming (MIP) model to address chemical production scheduling problems in a wide range of facilities, including facilities with many different types of material handling restrictions and a wide range of process characteristics. We first discuss how material handling restrictions result in different types of production environments and then show how these restrictions can be modeled. We also present extensions for some important processing constraints and briefly discuss how other constraints and characteristics can be modeled. Finally, we present constraint propagation methods for the calculation of parameters that are used to formulate tightening constraints that lead to a substantial reduction of computational requirements. The proposed model is the first to address the generalized chemical production scheduling problem