结合能耗成本的双资源混合流程生产多目标调度优化研究

Energy consumption takes a big portion of the total costs of manufacturing companies and it is also one of main reasons to environment pollution. With the control requirements of energy consumption, production scheduling in manufacturing systems are highly important and complicated. This project is to study the optimization of production scheduling problem in the hybrid flow-shop environment with dual resources and with the considering of energy consumption cost, by employing various techniques including mathematical programming, multi-objective optimization and artificial intelligence based algorithms. The core research contents include: (1) the project is to study the integration optimization model of hybrid flow-shop production scheduling problem with dual resources coupling and the energy consumption cost. After clarifying the key objectives and constraints of the problem, the multiple-objective integrated mathematical model will be developed, based on which, the analytical analysis of the model will be further conducted. (2) The inherent feature of the mathematical model and the set-partitioning reformulation will be analyzed. Then, the project is to study the optimization solving methods of integrated scheduling problem with the branch and bound, and the branch and price algorithm. (3) For large scale problems, the project is to develop meta-heuristic methods with the multi-objective tabu search algorithm in which the multi-path search and the idea of pareto optimization are integrated. Moreover, the effectiveness and efficiency of method will be analyzed through practical data from industry and experimental simulation. The study of the project is quite helpful for model building, the theory of optimization and systematic solutions to the integrated optimization problem of production scheduling and energy consumption cost with the consideration of dual resources coupling. It is, to some extent, can also deepen the theory of production scheduling and can also guide potential practical applications. Meanwhile, the study of the project is supposed to improve the utilization of the manufacturing resources and improve the energy effective manufacturing, which in turn can give some insights for better operational decisions in production systems.

能源消耗既是制造企业的重要成本，也是环境污染的主要原因之一。针对能源消耗控制需求下生产调度优化的重要性和复杂性，本项目综合运用数学规划、多目标优化以及人工智能算法对结合能耗成本的双资源混合流程生产调度问题进行优化研究。主要研究内容为：（1）研究具有双资源耦合的混合流程生产调度与能耗成本集成模型，在厘清优化目标和关键约束基础上，建立调度问题多目标集成优化数学模型，并对模型进行理论解析分析；（2）基于问题性质和集合划分等价建模，开发结合分支定界和分支定价算法的高效精确求解方法；（3）针对较大规模复杂问题，研究基于多路径Pareto禁忌搜索的启发式算法，并通过企业实践和仿真实验，分析求解性能。本项目的研究有助于建立结合能耗成本的双资源混合流程生产调度的建模、优化理论和方法体系，对调度管理理论的深化和拓展应用具有一定的贡献，对提高资源运营效率和能耗效益，进而对提升生产系统科学决策也具有积极的意义。

本项目根据既定的研究计划，综合运用调度理论、混合整数规划、多目标优化、分支定界(价)以及人工智能算法对结合能耗成本的生产调度问题展开了深入系统的研究，并取得了一系列成果。依照项目研究计划，重点研究了考虑碳排放的面向玻璃生产和汽车模具铸件生产的各类制造调度问题，包括两阶段混合流水线问题、并行机问题、单机批量和两机流水线问题等；基于问题性质和集合划分等价建模，研究开发结合分支定界和分支定价算法的高效精确求解方法；此外，也对其他密切相关的扩展问题进行了研究，包括考虑能耗的库存管理问题，结合能耗的车辆路径问题和结合鲁棒特性的调度问题等。上述研究中的一部分成果是结合生产企业实际情况提炼出的相应调度模型，以及有效策略和方法的设计与结论分析，另一部分成果则是对已有研究结论的改进。2016-2019年间发表和在线发表了标注项目基金号71571135的学术论文共24篇，其中SCI检索期刊论文15篇，CSSCI期刊1篇，国际会议论文6篇，参加国际会议8人次，培养学术型硕士生4位，博士生1位。圆满完成了项目拟定的四年发表10-15篇、国际期刊SCI收录4-6篇、国际会议论文2-4篇的任务。发表的成果中包括管理领域核心期刊《Computers & Operations Research》、《International Journal of Production Research》和《Journal of Cleaner Production》等。