کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5082033 | 1477622 | 2009 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A bicriteria approach to minimize number of tardy jobs and resource consumption in scheduling a single machine
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی صنعتی و تولید
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: A bicriteria approach to minimize number of tardy jobs and resource consumption in scheduling a single machine A bicriteria approach to minimize number of tardy jobs and resource consumption in scheduling a single machine](/preview/png/5082033.png)
چکیده انگلیسی
We extend the classical scheduling problem of minimizing the number of tardy jobs in a single-machine to the case where the job processing times are controllable by allocating a continuous and non-renewable resource to the processing operations. Our aim is to construct an efficient trade-off curve between the number of tardy jobs and total resource consumption using a bicriteria approach. Most of the research on scheduling with controllable resource-dependent processing times is done either to a linear resource consumption function or to a specific type of convex resource consumption function. We, in contrast, analyze the problem for a more general type of convex decreasing resource consumption function, which guarantees a very robust analysis that can be applied to a wide range of problems. We present four different variations of the problem and prove them to be NP-hard. We then present a polynomial time algorithm to solve an important special case of the problem and also suggest and compare the performances of three different heuristic algorithms.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Production Economics - Volume 119, Issue 2, June 2009, Pages 298-307
Journal: International Journal of Production Economics - Volume 119, Issue 2, June 2009, Pages 298-307
نویسندگان
Liron Yedidsion, Dvir Shabtay, Ephraim Korach, Moshe Kaspi,