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机构地区:[1]中南大学商学院,长沙410083 [2]西安交通大学管理学院,西安710049
出 处:《系统工程理论与实践》2016年第4期923-933,共11页Systems Engineering-Theory & Practice
基 金:国家自然科学基金委重大国际(地区)合作与交流项目(71210003);中南大学博士后科研资助项目;国家自然科学基金(71501194)~~
摘 要:在混流装配线中,需求波动会造成工位负荷的变化并可能产生过载,利用多能工协助装配是解决过载问题的常见方法.多能工的引入会改变装配线平衡的约束,同时平衡方案也会影响应对需求波动所需的多能工数量,然而现有的平衡研究还没有讨论过多能工带来的影响.本文研究了使用多能工应对需求变化的混装线平衡问题,决策者需要决定多能工和普通工人的数量及任务分配.以最小化人工成本并满足不同情境的需求.文章建立了数学模型,分析了问题的复杂性和成本下界,并提出了启发式和精确算法来求解,最后使用数值实验证明了算法的有效性.In a mixed model assembly line, when demands for different products vary, the workload of stations will change and sometimes work overload may occur. Hiring utility workers to help ordinary workers in case of work overload is a common practice in just-in-time (JIT) production systems, and will affect the constraints and objective of assembly line balancing problem, but no study has ever discussed it. This paper aims to design a mixed model assembly line with utility workers to satisfy uncertain demands in all possible scenarios. The decision maker needs to determine the number of utility workers and ordinary workers, and their tasks allocation in order to minimize the total labor cost. This problem is formulated as a mixed integer programming and is proved NP-complete. A method to estimate the lower bound on labor cost is presented, based on which a heuristic and a branch, bound and remember algorithm are proposed. The numerical experiments on 500 instances show that the proposed algorithms are effective and efficient.
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