基于组合缓冲的分布式置换流水车间调度优化  

Distributed permutation flow shop scheduling optimisation with combined-buffer

作　　者：轩华 吕琳 XUAN Hua;LÜLin(School of Management,Zhengzhou University,Zhengzhou 450001,China)

机构地区：[1]郑州大学管理学院,郑州450001

出　　处：《现代制造工程》2025年第1期1-14,共14页Modern Manufacturing Engineering

基　　金：国家自然科学基金资助项目(U1804151);河南省科技攻关计划项目(232102321093,232102321026);河南省哲学社会科学规划项目(2023BJJ085)。

摘　　要：针对制造行业中机器间有两种缓冲条件(即有限缓冲、零等待)的分布式置换流水车间调度问题,以最小化最大完工时间作为目标建立数学规划模型,提出了一种结合改进两分段Tent混沌映射、自适应柯西变异和贪婪算法的混合人工蜂群算法。首先,通过改进两分段Tent混沌映射产生初始工件序列群;然后,在雇佣蜂阶段采用基于自适应柯西变异的邻域搜索产生新工件序列,在跟随蜂阶段设计适应度选择策略和基于自适应柯西变异的逆序反转操作对工件序列进行优化,在侦察蜂阶段利用贪婪算法基于关键/非关键工厂更新未改善的工件序列;最后,通过大量算例仿真与多种算法对比,表明所提算法在合理的计算时间内可以得到较好的近优解。The permutation flow shop problem with two inter-machine buffer conditions(i.e.limited buffer,zero-wait) is studied arising from manufacturing industry,and a mathematical programming model is established with the objective of minimizing maximum completion time.A mixed artificial bee colony algorithm is then proposed combined with improved two-segment Tent chaotic mapping,adaptive Cauchy mutation and greedy algorithm.Firstly,the initial job sequence population is generated by improving two-segment Tent chaotic mapping.Then,in the employed bee phase,the neighborhood search based on adaptive Cauchy mutation is applied to generate new job sequences.In the onlooker bee stage,a selection fitness strategy and the inverse-order reversal operation based on adaptive Cauchy mutation are designed to optimize the job sequences.In the scout bee phase,unimproved job sequence is updated based on key/non-key factories by greedy algorithm.Finally,a large number of simulations and comparisons with various algorithms show that the proposed algorithm can obtain a good near-optimal solution in a reasonable computational time.

关 键 词：分布式置换流水车间调度 有限缓冲和零等待 混合人工蜂群算法 改进两分段Tent混沌映射 自适应柯西变异 

分 类 号：TB49[一般工业技术]