Abstract: Integrated production and distribution scheduling is an important direction for manufacturing enterprises to achieve cost reduction and efficiency increase from the perspective of supply chain.For a flexible assembly flowshop scheduling and batch distribution integration problem including three stages of processing,partial assembly and final assembly,complex schedule coordination needs between multiple orders at the same address and multi-layer parts under the same order are considered.A mixed integer programming model is established to minimize the sum of finished product inventory cost,delivery batch cost and order delay cost.Based on the characteristics of the problem,an improved grey wolf optimizer algorithm embedded with adaptive evolutionary population dynamic operators is designed.The hierarchical coupling constraints reflecting the strict dependency relationship among finished products,components and parts are integrated into the encoding and decoding of the algorithm,in order to realize the deep search in the feasible domain at all times.Finally,based on the characteristics of actual production data,dozens of examples are generated from multiple dimensions,and the results of comparison with solvers and related intelligent algorithms show the advantages of the proposed algorithm.

Key words: integrated production and distribution scheduling, flexible assembly flowshop, hierarchical coupling constraints, grey wolf optimizer

摘要： 生产与配送集成调度是当前制造企业从供应链视角下实现降本增效的重要方向,针对一类包含加工-部装-总装三个阶段的柔性装配流水车间调度与分批配送集成问题,考虑同地址多个订单之间和同订单多层零部件之间的复杂进度协同需求,以最小化成品库存成本、配送批次成本和订单拖期成本之和为目标建立了混合整数规划模型。结合问题特征,设计了一类嵌入自适应进化种群动态算子的改进型灰狼优化算法,其将体现成品、部件和零件之间严格从属关系的分层耦合约束集成到算法的编码和解码中,以实现算法始终在可行域内进行深度搜索。最后,基于实际生产数据特征,从多个维度生成了数十个算例,与求解器和相关智能算法的对比结果表明了所提算法的优势。

关键词: 生产与配送集成调度, 柔性装配流水车间, 分层耦合约束, 灰狼优化算法