Threat elimination algorithm for Dual Resource Constrained Flexible Job Shop Scheduling Problems

Abstract

This paper proposes an expert knowledge based algorithm for solving the Dual Resource Constrained Job Shop Scheduling Problem (DRC-FJSSP), the Biggest Threat First (BTF). The main idea behind this algorithm is that by eliminating your biggest threat, you get much closer to achieving your goal. Moreover, the BTF algorithm considers an encoded representation of the schedule, which combines 2 vectors: the Blacklist and the Deployment. The Blacklist sorts the major threats in descending order, while the Deployment vector allocates a worker-machine pair to tackle each assigned task. Results show that this method utterly outperforms a state-of-the-art metaheuristic, the KGFOA, at makespan minimization problems when applied to the MK1-10 benchmark dataset. Future work may access the algorithm's performance in problems with different performance metrics, such as the weighted tardiness. Moreover, research may be carried to apply the BTF to problems where the processing time of operations varies with the allocated worker-machine pair.