复杂约束再制造调度及基于协作策略的离散智能算法研究

In recent years, Re-manufacturing scheduling has been researched by more and more people in academic and industry fields. Re-manufacturing scheduling includes three parts, e.g. disassemble scheduling, re-processing scheduling and re-assemble scheduling. Most existing re-manufacturing scheduling researches focus on overall theoretical approach, with mainly mathematical modelling and simulations which are not associated with any kind of specific re-manufacturing operation. In fact, because most studies are theoretical, the need for more practical research on re-manufacturing scheduling with complex constraints is evident. The goal of this project is to research the re-manufacturing scheduling with complex constraints and practical applications. Firstly, we will analyse the characteristics and constraints of re-manufacturing, design effective encoding and decoding methods, research on the neighborhood of re-manufacturing scheduling, design simple heuristics. Secondly, we will research on the Teaching-and-learning based optimization (TLBO) and Jaya (Meaning victory in Sanskrit) algorithms, and design ensembles of heuristics, neighborhood search operators, TLBO and Jaya algorithms to improve algorithms’ performance. Thirdly, we will develop ensembles of algorithms for solving re-manufacturing scheduling problems with complex constraints and multiple objectives, research on the rescheduling strategies and rescheduling algorithms for the uncertainty of processing time and new job(s) insertion constraints. Finally, the research achievements will be applied to real-life applications for pump re-manufacturing. Some feedback can obtained to enhance and improve the re-manufacturing scheduling theory and methods.

近年来，再制造调度 (re-manufacturing scheduling) 问题引起国内外学术界和工业界的广泛关注。再制造调度问题主要面向再制造的三个阶段：回收产品的拆分调度、可修复部件再加工调度和产品重组装调度。现有研究还很不完善，主要集中在理论分析和建立模型，缺少考虑实际复杂约束，难以有效应用于生产实践。本项目拟研究复杂约束再制造调度问题。结合问题特征、约束条件和求解目标，建立高性能编码和解码方法、分析邻域结构、设计启发式算法；集成启发式算法、邻域搜索、教与学算法(TLBO)、征服算法(Jaya)等多种算法优势，设计基于协作策略的离散智能算法；研究再制造调度理论与方法，动态重调度策略及算法；求解单目标及多目标再制造调度及动态重调度问题；形成一系列具有实际工程应用价值的再制造调度及动态重调度方法和算法，可望直接服务于水泵再制造企业的实际调度问题，并通过实践反馈提高再制造调度理论与方法

再制造是对废旧产品实施高技术修复和改造的生产过程，它针对的是损坏或即将报废的零部件，在性能失效、寿命评估等分析的基础上，进行再制造工程设计，采用一系列相关的先进制造技术，使再制造产品质量达到或超过新品。再制造调度是实现再制造生产过程的合理安排与生产资源的优化配置，减少物耗和能耗，促进再制造生产过程的合理化、信息化和集成化的必要且有效地手段。再制造调度能保证调度方案的质量，满足生产效率和生产成本等性能指标的要求。.本项目以离散群智能算法为工具，包括和声搜索算法和Jaya算法等，对再制造调度问题研究。对复杂约束下的再制造过程调度问题建模并求解；算法设计方面，整合离散群智能算法和启发式算法、邻域搜索算法的优势，提高了算法性能。实际应用方面，研究并求解了大型水泵再制造过程的实际案例。项目研究过程取得了一系列具有较大创新性的研究成果，形成较高水平的理论成果。共完成相关学术论文19篇，其中SCI论文14篇，EI论文5篇，ESI高被引论文3篇，热点论文1篇。组织国际会议专题1次，参加国际会议并做主题报告1次，论文展示报告多次，培养研究生4名。实际应用方面，研究并求解了大型水泵再制造过程的实际案例。