Discrete Multi-Objective Grey Wolf Algorithm Applied to Dynamic Distributed Flexible Job Shop Scheduling Problem with Variable Processing Times

Applied Sciences, Год журнала: 2025, Номер 15(5), С. 2281 - 2281

Опубликована: Фев. 20, 2025

Uncertainty in processing times is a key issue distributed production; it severely affects scheduling accuracy. In this study, we investigate dynamic flexible job shop problem with variable (DDFJSP-VPT), which the time follows normal distribution. First, mathematical model established by simultaneously considering makespan, tardiness, and total factory load. Second, chance-constrained approach employed to predict uncertain generate robust initial schedule. Then, heuristic method involves left-shift strategy, an insertion-based local adjustment DMOGWO-based global rescheduling strategy developed dynamically adjust plan response context of uncertainty. Moreover, hybrid initialization scheme, discrete crossover, mutation operations are designed high-quality population update wolf pack, enabling GWO effectively solve problem. Based on parameter sensitivity study comparison four algorithms, algorithm’s stability effectiveness both static environments demonstrated. Finally, experimental results show that our can achieve much better performance than other rules-based reactive methods hybrid-shift strategy. The utility prediction also validated.

Язык: Английский

Distributed heterogeneous flexible job-shop scheduling problem considering automated guided vehicle transportation via improved deep Q network

Swarm and Evolutionary Computation, Год журнала: 2025, Номер unknown, С. 101902 - 101902

Опубликована: Март 1, 2025

Язык: Английский

A lot streaming scheduling algorithm with variable sub-lots for solving a multi-objective flexible job shop scheduling problem

Applied Soft Computing, Год журнала: 2025, Номер 177, С. 113184 - 113184

Опубликована: Апрель 28, 2025

Язык: Английский