A Study on Improving the Golden Jackal Optimization Algorithm to Solve the Flexible Workshop Scheduling Problem

This study present an improved golden jackal optimization algorithm (IGJO) to address the flexible job shop scheduling problem (FJSP) with the primary purpose of maximizing minimization. The study employs a two-stage coding approach to establish the connection between the algorithm and scheduling. Additionally, an elite reverse strategy is employed to enhance the quality of the initial solution. Furthermore, a nonlinear convergence factor is introduced to ensure a balanced search function of the algorithm. In the position update phase, a position update method based on the fitness value is proposed. Finally, the effectiveness of the IGJO algorithm in addressing the FJSP problem is verified through a benchmark example.