Single Machine CON/SLK Due Date Assignment Scheduling with Controllable Processing Time and Job-dependent Learning Effects

2017 ◽  
Vol 61 (9) ◽  
pp. 1329-1337 ◽  
Author(s):  
Ji-Bo Wang ◽  
Xin-Na Geng ◽  
Lu Liu ◽  
Jian-Jun Wang ◽  
Yuan-Yuan Lu
2013 ◽  
Vol 645 ◽  
pp. 280-284
Author(s):  
Hua Ping Wu ◽  
Min Huang ◽  
Vincent Cho ◽  
W.H. Ip ◽  
Xing Wei Wang

The paper considers the due-date assignment problem with a non-linear deterioration in which the due dates are determined by the equal slack method. Here, the processing time of a job is defined by a non-linear function of total normal processing time of jobs in front of it in the sequence. The objective is to minimize the total tardiness penalties. According to the needs from the real world, the problem is divided into two cases, i.e., allowing with early jobs and no early jobs respectively. The related lemma, corollary and theorems for the problems are proposed and proved. At the same time, it shows that the problems in this paper can be solved in the polynomial times.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Li-Yan Wang ◽  
Mengqi Liu ◽  
Ji-Bo Wang ◽  
Yuan-Yuan Lu ◽  
Wei-Wei Liu

In this paper, the single-machine scheduling problem is studied by simultaneously considering due-date assignment and group technology (GT). The objective is to determine the optimal sequence of groups and jobs within groups and optimal due-date assignment to minimize the weighted sum of the absolute value in lateness and due-date assignment cost, where the weights are position dependent. For the common (CON) due-date assignment, slack (SLK) due-date assignment, and different (DIF) due-date assignment, an O n    log    n time algorithm is proposed, respectively, to solve the problem, where n is the number of jobs.


2009 ◽  
Vol 2009 ◽  
pp. 1-10 ◽  
Author(s):  
Kaibiao Sun ◽  
Hongxing Li

This paper addresses a single-machine problem in which the past-sequence-dependent (p-s-d) setup times and exponential time-dependent and position-dependent learning effects are considered. By the exponential time-dependent learning effect, it means that the processing time of a job is defined by an exponent function of the total actual processing time of the already processed jobs. The setup times are proportional to the length of the already processed jobs. The aim is to minimize the total weighted completion time, this is an NP-hard problem. Under certain conditions, it is shown that the classical WSPT rule is optimal for the problem.


2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Chuan-Li Zhao ◽  
Chou-Jung Hsu ◽  
Hua-Feng Hsu

This paper considers single machine scheduling and due date assignment with setup time. The setup time is proportional to the length of the already processed jobs; that is, the setup time is past-sequence-dependent (p-s-d). It is assumed that a job's processing time depends on its position in a sequence. The objective functions include total earliness, the weighted number of tardy jobs, and the cost of due date assignment. We analyze these problems with two different due date assignment methods. We first consider the model with job-dependent position effects. For each case, by converting the problem to a series of assignment problems, we proved that the problems can be solved inOn4time. For the model with job-independent position effects, we proved that the problems can be solved inOn3time by providing a dynamic programming algorithm.


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