Scheduling in dynamic assembly job-shops with jobs having different holding and tardiness costs
Scheduling in dynamic assembly job-shops with jobs having different holding and tardiness costs
复制标题
DOI：
10.1080/00207540310001595864
复制
发表时间：
2003-12
影响因子：
9.2
通讯作者：
S. Thiagarajan;C. Rajendran
中科院分区：
文献类型：
--
作者：
S. Thiagarajan;C. Rajendran
大多数动态车间调度问题的研究假设工件的等待成本由工件的流动时间决定，工件的拖期成本由工件的拖期决定。换句话说，单位持有和单位拖期成本的工作是假设。然而，在现实中，这样的假设不一定成立，而且很可能不同的工作有不同的等待和延误成本。此外，大多数车间作业调度的研究假设工件是独立的，不存在装配操作。本文研究了动态装配车间（制造多层工件）中的调度问题，考虑了不同工件的等待和拖期成本。试图通过将工件的相对持有成本和拖期成本以标量权重的形式结合起来，来开发有效的调度规则。这里考虑的调度的主要目标是最小化的总调度成本组成的持有和拖期成本的总和。调度规则的性能在最小化的总调度成本的各个组件也被观察到。对不同调度规则的性能进行了广泛的模拟研究，结果表明，所提出的规则在最小化主要措施的均值和最大值方面是有效的，并且对于不同的作业结构和实验设置是相当鲁棒的。
Most studies on scheduling in dynamic job-shops assume that the holding cost of a job is given by the flowtime of the job and that the tardiness cost of a job is given by the tardiness of the job. In other words, unit holding and unit tardiness costs of a job are assumed. However, in reality, such an assumption need not hold, and it is quite possible that there are different costs for holding and tardiness for different jobs. In addition, most studies on job-shop scheduling assume that jobs are independent and that no assembly operations exist. The current study addresses the problem of scheduling in dynamic assembly job-shops (manufacturing multilevel jobs) with the consideration of different holding and tardiness costs for different jobs. An attempt is made to develop efficient dispatching rules by incorporating the relative costs of holding and tardiness of jobs in the form of scalar weights. The primary objective of scheduling considered here is the minimization of the total scheduling cost consisting of the sum of holding and tardiness costs. The performance of the scheduling rules in minimizing the individual components of total scheduling cost is also observed. The results of an extensive simulation study on the performance of different dispatching rules show that the proposed rules are effective in minimizing the means and maximums of the primary measure, and are quite robust with respect to different job structures and experimental settings.