Infeasibility resolution for multi-purpose batch process scheduling

Abstract

Scheduling decisions give rise to some of the most challenging optimization problems in the process industry. Formulating mathematical models for scheduling problems and devising tailored solution algorithms for these models has been the main thrust of previous literature. In this work, we focus on analyzing and resolving the cause of bottlenecks and infeasibilities in generic scheduling problems. We present a systematic approach for infeasibility diagnosis. Our approach exploits the known structure of scheduling models to isolate interpretable infeasible sets of constraints. We demonstrate the power of the algorithm on infeasible instances of the Westenberger–Kallrath multipurpose batch process modeled using a state-task network (STN) representation. The methodology presented in the paper is able to successfully analyze the cause of infeasibility and provide recommendations for resolving it. We also demonstrate how these insights and recommendations can be presented to scheduling operators with little or no optimization expertise in an intuitive manner.