转包商选择与单机批调度联合优化  

Joint Optimization of Subcontractor Options and Single-machine Batch Scheduling

作　　者：唐文娜 刘乐 TANG Wen-Na;LIU Le(Business School,University of Jinan,Jinan 250002,China)

机构地区：[1]济南大学商学院,济南250002

出　　处：《计算机系统应用》2022年第9期342-351,共10页Computer Systems & Applications

基　　金：国家自然科学基金(71501083);山东省自然科学基金面上项目(ZR2020MG007);中国博士后科学基金面上项目(2019M662296);济南大学社科类校级项目(19YB03)。

摘　　要：面向多转包商的外包选择是当今制造企业面临的一大运营管理挑战.它与内部作业调度的一体化决策对企业降本增效至关重要.本文针对有多个转包商可供作业外包选择的单机批调度联合优化问题,在外包总成本和外包作业最晚交付期均受上限前提下建立以最小化外包总成本与内部批加工总成本之和为目标的0-1整数规划模型,并为该问题设计了改进型遗传算法和贪婪算法.以某陶瓷企业的外包与批调度联合决策场景为实例,对比分析了这两种算法的求解性能,发现改进型遗传算法在求解质量和时间上具有比较优势.在模型的灵敏度实验分析中发现,外包作业最晚交付期对作业运营总成本有显著影响,而作业外包总成本的给定上限值对作业运营总成本的影响不显著.Outsourcing with multiple subcontractors is a major operational management challenge for today’s manufacturing firms. The joint decision-making between outsourcing options and in-house scheduling is crucial to the cost reduction and efficiency increase of these firms. To jointly optimize single-machine batch scheduling with multiple subcontractors available for job outsourcing, this study constructs a 0-1 integer programming model, the objective of which is to minimize the sum of total outsourcing cost and total in-house batch processing cost under the premise that both the total outsourcing cost and the latest leading time for outsourcing jobs are subject to upper limits. An improved genetic algorithm and a greedy algorithm are also designed for joint optimization. The study takes the joint decisionmaking scenario of outsourcing and batch scheduling in a ceramic enterprise as an example and compares the solution performance of the two algorithms. The improved genetic algorithm shows its comparative advantages in terms of solution quality and efficiency. The results of a sensitivity experiment show that the latest leading time for outsourcing jobs has a significant impact on the total operating cost, while the upper limit of the total outsourcing cost does not significantly influence the total operating cost.

关 键 词：调度优化 外包 多转包商 批处理机 遗传算法 批调度 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] F274[自动化与计算机技术—控制科学与工程]