Solving a Job Shop Scheduling Problem with Recurring Tasks and Dominant Processing Time

Lee Li Yee Serene

Abstract

.This study introduces an optimization model developed to address a Job Shop Scheduling Problem (JSSP) with a focus on scenarios featuring recurring tasks and significant disparities in processing times, termed as 'dominant processing time'. Utilizing Mixed-Integer Linear Programming (MILP) and leveraging the Gurobi optimizer, the model achieves a substantial improvement in scheduling efficiency by minimizing the total makespan. Key innovations include the strategic integration of a dynamic Big M calculation to enhance optimization efficiency and the model's adeptness at managing varying processing times. The findings demonstrate the model's robust applicability across diverse manufacturing scenarios, offering a scalable and adaptable solution to complex JSSP variants.