Slack Due-Window Assignment Scheduling Problem with Deterioration Effects and a Deteriorating Maintenance Activity

Author(s):  
Xue Jia ◽  
Dan-Yang Lv ◽  
Yang Hu ◽  
Ji-Bo Wang ◽  
Zhi Wang ◽  
...  

This paper studies the slack due-window assignment scheduling problem with deterioration effects and a deterioration maintenance activity on a single-machine. The machine deteriorates during the machining process, and at a certain moment performs a deterioration maintenance activity, that is, the duration time of the maintenance activity is a linear function of the maintenance starting time. It is needed to make a decision on when to schedule the deteriorating maintenance activity, the optimal common flow allowances and the sequence of jobs to minimize the weighted penalties for the sum of earliness and tardiness, weighted number of early and delayed, and weighted due-window starting time and size. This paper proposes a polynomial time algorithm to solve this problem.

2020 ◽  
Vol 2020 ◽  
pp. 1-7 ◽  
Author(s):  
Li-Yan Wang ◽  
Dan-Yang Lv ◽  
Bo Zhang ◽  
Wei-Wei Liu ◽  
Ji-Bo Wang

This paper considers a single-machine due-window assignment scheduling problem with position-dependent weights, where the weights only depend on their position in a sequence. The objective is to minimise the total weighted penalty of earliness, tardiness, due-window starting time, and due-window size of all jobs. Optimal properties of the problem are given, and then, a polynomial-time algorithm is provided to solve the problem. An extension to the problem is offered by assuming general position-dependent processing time.


2014 ◽  
Vol 31 (05) ◽  
pp. 1450036 ◽  
Author(s):  
Ji-Bo Wang ◽  
Ming-Zheng Wang

We consider a single-machine common due-window assignment scheduling problem, in which the processing time of a job is a function of its position in a sequence and its resource allocation. The window location and size, along with the associated job schedule that minimizes a certain cost function, are to be determined. This function is made up of costs associated with the window location, window size, earliness, and tardiness. For two different processing time functions, we provide a polynomial time algorithm to find the optimal job sequence and resource allocation, respectively.


2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Yu-Bin Wu ◽  
Ping Ji

We consider a common due-window assignment scheduling problem jobs with variable job processing times on a single machine, where the processing time of a job is a function of its position in a sequence (i.e., learning effect) or its starting time (i.e., deteriorating effect). The problem is to determine the optimal due-windows, and the processing sequence simultaneously to minimize a cost function includes earliness, tardiness, the window location, window size, and weighted number of tardy jobs. We prove that the problem can be solved in polynomial time.


Author(s):  
chen xu ◽  
Yinfeng Xu ◽  
Feifeng Zheng ◽  
Ming Liu

We study multitasking scheduling and due-window assignment problems in a single machine, which can be found in various application domains.In this paper, we study two problems, the rst objective is minimise the earliness, tardiness, due-window starting time, and due-window size costs, the second objective is minmax common due-date with completion time penalty, then we provide polynomial time solutions. Finally, the experimental results show that the proposed methods are e ective.


2013 ◽  
Vol 344 ◽  
pp. 290-293
Author(s):  
Cheng Xin Luo

This paper studies single-machine scheduling problems with a due-window assignment under a deteriorating maintenance and time-and-resource-dependent processing times. Jobs completed within the due-window incur no penalties, other jobs incur either earliness or tardiness penalties. The maintenance activity can be scheduled immediately after any of the completed jobs. We assume that once the maintenance activity has been completed, the machine efficiency will be improved and the machine maintenance duration depends on its starting time. The objective is to find the maintenance position, the size and location of the due-window, and the sequence of jobs and resource allocation scheme to minimize a cost function based on the window size and location and the earliness and tardiness of jobs and resource. We propose an algorithm to solve the problem.


2014 ◽  
Vol 1006-1007 ◽  
pp. 437-440
Author(s):  
Wei Xuan Li ◽  
Chuan Li Zhao

This paper considers single machine scheduling with general position-dependent and job-dependent aging effect. All jobs share a common due window, and an optional maintenance activity (OMA) is taken into consideration. The processing time of a job is a non-decreasing function in its position. Such category of maintenance activity is called the OMA since one can determine the position and the actual duration of it. The objective is to determine the optimal due window position, the optimal location and duration of the OMA, and the optimal job sequence so as to minimize the total of earliness, tardiness, due window starting time, due window size, and the OMA duration related costs. We show that the considered problem can be solved in polynomial time.


2013 ◽  
Vol 278-280 ◽  
pp. 2248-2251
Author(s):  
Cheng Xin Luo

This paper studies single-machine scheduling problems with a due-window assignment and a rate-modifying activity under a deteriorating maintenance consideration simultaneously. Jobs completed within the due-window incur no penalties, other jobs incur either earliness or tardiness penalties. The maintenance activity can be scheduled immediately after any one of the completed jobs. We assume that once the maintenance activity has been completed, the machine efficiency will be improved and the machine maintenance duration depends on its starting time. The objective is to find the optimal maintenance position as well as the optimal size and location of the due-window, and the sequence of jobs to minimize a cost function based on the window size and window location and the earliness and tardiness of the jobs. We propose a polynomial time algorithm to solve the problem optimally.


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