Single-Machine Due-Window Assignment Scheduling with Resource Allocation and Generalized Earliness/Tardiness Penalties

Author(s):  
Yu Tian

In this study, the due-window assignment single-machine scheduling problem with resource allocation is considered, where the processing time of a job is controllable as a linear or convex function of amount of resource allocated to the job. Under common due-window and slack due-window assignments, our goal is to determine the optimal sequence of all jobs, the due-window start time, due-window size, and optimal resource allocation such that a sum of the scheduling cost (including weighted earliness/tardiness penalty, weighted number of early and tardy job, weighted due-window start time, and due-window size) and resource consumption cost is minimized. We analyze the optimality properties, and provide polynomial time solutions to solve the problem under four versions of due-window assignment and resource allocation function.

2015 ◽  
Vol 32 (03) ◽  
pp. 1550014 ◽  
Author(s):  
Chuanli Zhao ◽  
Hengyong Tang

This paper considers a single machine scheduling with both deterioration and positional effects and due-window assignment problem. The job-dependent due-windows are obtained by the common flow allowance criterion. The objective is to schedule the jobs, and the due-windows so as to minimize the sum of earliness, tardiness, and due-window starting time and due-window size costs. We introduce a polynomial solution for the problem. Furthermore, we show how the solutions can be extended to the setting with job rejection.


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 32 (06) ◽  
pp. 1550045 ◽  
Author(s):  
Shang-Chia Liu

This paper investigates a single-machine scheduling problem involving both the due-window assignment and position-dependent processing times under a group technology environment. By position-dependent processing times, we mean that the processing time of a job is dependent of its processing position in the job sequence within the group it belongs to. A setup time is incurred whenever the single machine transfers job processing from a group to another group. Each group is assigned an assignable common due-window. A job completed earlier (respectively, later) than the common due-window of the group it belongs to will incur an earliness (respectively, tardiness) penalty. The objective is to determine the optimal group sequence, the optimal job sequence, and the optimal due-window assignment so as to minimize the total cost including the earliness and tardiness (or weighted number of tardy jobs) penalties, black and the due-window starting time and due-window size costs. We show that both the problems can be solved in polynomial times.


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.


2017 ◽  
Vol 34 (04) ◽  
pp. 1750011 ◽  
Author(s):  
Zhusong Liu ◽  
Zhenyou Wang ◽  
Yuan-Yuan Lu

This paper considers the single machine scheduling with learning effect, resource allocation and deteriorating maintenance activity simultaneously. For the convex resource allocation consumption function, we provide a bicriteria analysis where the first (schedule) criterion is to minimize the total weighted sum of makespan, total completion time and total absolute differences in completion times, and the second (resource) criterion is to minimize the total weighted resource consumption. Our aim is to find the optimal resource allocations and job sequence that minimize the three different models of considering the two criterion. We show that these three models are polynomially solvable respectively.


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.


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