Minimization Makespan Problem With an Aging Effect Based on Improved Arithmetic Optimization Algorithms on Job Shop Machines - Gan, Tian-Meng; Zhang, Xin-Gong; Lin, Win-Chin; Wu, Chin-Chia (Communications in Mathematics and Applications, 2025)
The research delves into optimizing the Job Shop Scheduling Problem (JSSP) by considering aging effects and release time. This paper introduces an Advanced Arithmetic Optimization Algorithm (IAOA) designed specifically to minimize the makespan. IAOA operates by translating the continuous solution space into the discrete realm of JSSP through ROV transformation rules. It encodes and decodes the job shop problem using an insertion greedy decoding algorithm. To refine the conventional Arithmetic Optimization Algorithm (AOA), this study introduces a nonlinear Mathematical Acceleration Function (MOA) along with six neighborhood search strategies. Evaluating its performance involved a comparison of IAOA against AOA, Grey Wolf Optimizer (GWO), and Arithmetic Trigonometric Optimization Algorithm (ATOA) across 33 benchmark problems. The experimental results underscore IAOA’s superior optimization efficacy and its ability to converge efficiently when dealing with JSSP. Notably, IAOA successfully mitigates AOA’s limitations, particularly in achieving higher solution accuracy and faster convergence speed.
Keywords: Arithmetic Optimization Algorithm; Job-shop scheduling problems; Greedy decoding algorithm; Aging effect; Release time