关键词: 多阶段, 多层级, 模糊柔性作业车间, 加法优先度, 模因算法, 模糊偏好

Abstract: The Multi-stage Multi-level Fuzzy Flexible Job Shop Scheduling Problem (MMFFJSSP) commonly exists in enterprises with complex product hierarchies,diverse products and high process requirements.Existing methods that use single numerical features for fuzzy number operations and evaluations cause information loss of fuzzy numbers,resulting in significant changes in the ranking results and cannot guarantee the consistency and reliability of the outcomes.To address these issues,a fuzzy number ranking method based on Addition Priority of Fuzzy Preference Relation (APFPR) was proposed.Multidimensional features of the shapes and relative positions of fuzzy numbers were integrated by introducing fuzzy preference relations to avoid information loss and ranking deviations,enhancing the credibility of scheduling.In addition,a Multi-Strategy Adaptive Memetic Algorithm based on Fuzzy Fitness Gradient Selection (MSAMA-FFGS) was designed to solve the MMFFJSSP and minimize the maximum fuzzy completion time.In MSAMA-FFGS,adaptive crossover and mutation strategies based on fuzzy fitness were designed to dynamically adjust the algorithm operations,thus the search capabilities were improved.Critical products and job were identified to optimize components that impact overall completion time,which enhanced solution quality.Finally,the stability of APFPR in handling fuzzy number ranking problems was demonstrated by theoretical analysis and experimental results.The effectiveness of the proposed MSAMA-FFGS for solving the MMFFJSSP was verified by simulation comparison experiments.

Key words: multi-stage, multi-level, fuzzy flexible job shop, addition priority, memetic algorithm, fuzzy preference