Modeling and Solving an Extended Parallel Resource Scheduling Problem in the Automotive Industry

Abstract

This paper presents an extended model for solving time-varying resourceconstrained scheduling problems. The motivation for our research comes from the automotive industry. The problem is to create fine schedules for a complex manufacturing system to satisfy diverse customer demands. The detailed characteristics of the analyzed scheduling problem and the developed solving approach are described in this paper. To consider the impact of the assistant processes that are connected to the manufacturing primary processes, we elaborated a problem-transformation procedure and a new extended scheduling model that can manage time-varying availability constraints of parallel resources, unit processing times, job-dependent release times and due dates. This paper also presents slack-oriented and JIT-oriented algorithms that can solve the resourceconstrained scheduling problems. The research results have been successfully applied and tested in practice.