Abstract

This paper proposes a genetic algorithm (GA) for the Dual-Resource Flexible Job Shop Scheduling Problem with Partial Resource Allocation (DRFJSSP-PRA), a particular variant of a dual-resource constrained scheduling problem that has not been fully explored due to its intricate nature. The DRFJSSP-PRA poses a challenging scheduling problem, having several applications in many industries, including food, chemistry and pharmaceutics. The proposed algorithm is applied to real-world scheduling instances in pharmaceutical quality control. The objective function considered is the total completion time. The GA is compared with three state-of-the-art algorithms. For small- and medium-size instances, the proposed algorithm achieves optimal or near optimal results for the majority of the instances tested. For large-sized instances, the proposed GA outperforms all the other algorithms, in all of the tested instances. Thus, the experimental results show that the proposed GA achieves competitive results for any type of instance. The proposed algorithm also has the ability to optimize production processes through scheduling, leading to potential cost savings, increased efficiency, and improved competitiveness.

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