Dual Resource Constrained Scheduling for Quality Control Laboratories

Abstract

This work presents a novel formulation for quality control laboratory scheduling considering both equipment and analysts as constraints. The problem is modelled as a dual-resource constrained flexible job shop problem. The formulation considers analyst tasks at different times during the processing of samples. The problem is formulated as a mixed integer linear programming model (MILP) aiming to minimise makespan. Two sets of instances for the scheduling problem are proposed. The first instance consists of a small example that illustrates the proposed formulation and is solved to optimality. The second instance mimics the real industrial problem and shows the challenges resulting from growing complexity.