Interval Multi-Objective Multi-task Production Scheduling Method For Manufacturing Uncertainty

As manufacturing enterprises face increasingly complex production scales and actual workshop environments, they may encounter challenges such as multiple order scheduling, disruptions from uncertain factors, and conflicts between objective functions. Therefore, this paper considers electricity price volatility and develops an interval function based on equipment cost uncertainty. Subsequently, to address the simultaneous scheduling demands of multiple orders, the model is formulated as a multitask optimization framework based on distinct production order characteristics. Next, this paper is tailored to the forging and machining production operations of actual workpiece manufacturing, and an interval multi-objective multi-tasking scheduling optimization model is constructed to address enterprise multi-order production. This model includes objective functions such as completion time, energy consumption, and uncertain production costs. Second, we proposed an adaptive transfer probability-based multifactorial evolutionary algorithm (ATP-MFEA). Considering the independence of different production order scheduling processes and the similarity of workpiece products, a mechanism is designed to control the parameter of knowledge transfer probability based on the hypervolume metric, thereby enhancing algorithm performance. Finally, simulation experiments were conducted using actual data from a Chinese manufacturing enterprise specializing in workpieces. The results indicate that the constructed model has certain feasibility, and the designed algorithm demonstrates satisfactory performance