Harris Hawks Optimization Algorithm for Dual-Resource Constrained Flexible Job Shop Scheduling Problem with Makespan Criterion

Over the past few years, there has been a growing trend in the research community to focus on the scheduling problems associated with resource constraints. This paper deals specifically with the Dual-Resource Constrained Flexible Job shop Scheduling Problem (DRCFJSP), which is a well-known NP-hard problem. This problem is aimed at minimizing the maximum time to complete, commonly referred to as the makespan, due to its significance in research work-shops. The DRCFJSP considers the adaptability of both machinery and employees. However, traditionally, it has only considered machines as limited resources, neglecting the flexibility of workers. To address this issue and emphasize the importance of the problem, This paper presents a bio-inspired optimization algorithm named Harris Hawks Optimizer (HHO). Because of its effectiveness and simplicity of use, the HHO algorithm has garnered significant attention from researchers since its introduction. To assess the efficacy of the HHO algorithm, we compared it with the Multi-Start Tabu Agents-based Model (MuSTAM) on FJSPW benchmark instances created by Gong. The findings reveal that HHO typically generates superior solutions compared to MuSTAM.