Common Due-Window Assignment and Group Scheduling with Position-Dependent Processing Times

2015 ◽  
Vol 32 (06) ◽  
pp. 1550045 ◽  
Author(s):  
Shang-Chia Liu
Keyword(s):  
Single Machine ◽  
Group Technology ◽  
Window Size ◽  
Setup Time ◽  
Single Machine Scheduling ◽  
Processing Times ◽  
Weighted Number ◽  
Due Window ◽  
Tardy Jobs ◽  
Due Window Assignment

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.

scholarly journals Due-Window Assignment Scheduling with Variable Job Processing Times

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Yu-Bin Wu ◽  
Ping Ji
Keyword(s):  
Processing Time ◽  
Learning Effect ◽  
Window Size ◽  
Starting Time ◽  
Processing Times ◽  
Due Windows ◽  
Weighted Number ◽  
Due Window ◽  
Tardy Jobs ◽  
Due Window Assignment

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.

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

2021 ◽  
pp. 2150041
Author(s):  
Yu Tian
Keyword(s):  
Resource Allocation ◽  
Single Machine ◽  
Window Size ◽  
Single Machine Scheduling ◽  
Start Time ◽  
Optimal Sequence ◽  
Optimal Resource ◽  
Due Window ◽  
Weighted Earliness ◽  
Due Window Assignment

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.

Single Machine Scheduling and due Date Assignment with Past-Sequence-Dependent Delivery Times and General Position-Dependent Processing Times

2014 ◽  
Vol 624 ◽  
pp. 675-680
Author(s):  
Yu Fang Zhao
Keyword(s):  
Single Machine ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Scheduling Problems ◽  
Due Date ◽  
Due Date Assignment ◽  
Processing Times ◽  
Delivery Times ◽  
Weighted Number ◽  
Tardy Jobs

We studied single machine scheduling problems in which the jobs need to be delivered to customers after processing. It is assumed that the delivery times are proportional to the length of the already processed jobs, and a job's processing time depended 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 analyzed these problems with two different due date assignment methods and conclude that the problems are polynomial time solvable.

Due-Window Assignment for a Single Machine Scheduling with Both Deterioration and Positional Effects

2015 ◽  
Vol 32 (03) ◽  
pp. 1550014 ◽  
Author(s):  
Chuanli Zhao ◽  
Hengyong Tang
Keyword(s):  
Single Machine ◽  
Polynomial Solution ◽  
Window Size ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Due Windows ◽  
Due Window ◽  
Positional Effects ◽  
Due Window Assignment ◽  
Flow Allowance

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.

Single-Machine Due-Window Assignment and Scheduling with Learning Effect and Resource-Dependent Processing Times

2014 ◽  
Vol 31 (05) ◽  
pp. 1450036 ◽  
Author(s):  
Ji-Bo Wang ◽  
Ming-Zheng Wang
Keyword(s):  
Resource Allocation ◽  
Single Machine ◽  
Processing Time ◽  
Window Size ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Earliness And Tardiness ◽  
Processing Times ◽  
Due Window ◽  
Due Window Assignment

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.

Common Due Window Assignment Scheduling with Proportional Linear Deterioration Effects

2020 ◽  
Vol 37 (01) ◽  
pp. 1950031
Author(s):  
Xue Huang ◽  
Na Yin ◽  
Wei-Wei Liu ◽  
Ji-Bo Wang
Keyword(s):  
Window Size ◽  
Single Machine Scheduling ◽  
Scheduling Problems ◽  
Polynomial Time Algorithms ◽  
Linear Deterioration ◽  
Optimality Properties ◽  
Due Window ◽  
Tardy Jobs ◽  
Machine Scheduling Problems ◽  
Due Window Assignment

In this paper, single-machine scheduling problems with proportional linear deterioration effects and common due window assignment simultaneously are considered. Two different objective functions are studied, the first is to minimize the sum of the number of early jobs, number of tardy jobs and due window location and due window size, the second is to minimize the sum of the earliness cost, tardiness cost, due window location and due window size. Optimality properties for all problems are provided and polynomial time algorithms for solving these problems are given.

scholarly journals Scheduling with Learning Effects and/or Time-Dependent Processing Times to Minimize the Weighted Number of Tardy Jobs on a Single Machine

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Jianbo Qian ◽  
George Steiner
Keyword(s):  
Single Machine ◽  
Single Machine Scheduling ◽  
Time Dependent ◽  
Scheduling Problems ◽  
Processing Times ◽  
Number Of Tardy Jobs ◽  
Special Cases ◽  
Programming Techniques ◽  
Weighted Number ◽  
Tardy Jobs

We consider single machine scheduling problems with learning/deterioration effects and time-dependent processing times, with due date assignment consideration, and our objective is to minimize the weighted number of tardy jobs. By reducing all versions of the problem to an assignment problem, we solve them inO(n4) time. For some important special cases, the time complexity can be improved to beO(n2) using dynamic programming techniques.

Optimal Common Due-Window Assignment with Linear Deteriorating and Resource-Dependent Processing Times under a Deteriorating Maintenance Activitiy

2013 ◽  
Vol 344 ◽  
pp. 290-293
Author(s):  
Cheng Xin Luo
Keyword(s):  
Window Size ◽  
Single Machine Scheduling ◽  
Scheduling Problems ◽  
Maintenance Activity ◽  
Machine Maintenance ◽  
Processing Times ◽  
Deteriorating Maintenance ◽  
Due Window ◽  
Resource Allocation Scheme ◽  
Due Window Assignment

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.

Single Machine Due Window Assignment and Scheduling with an Optional Maintenance Activity

2014 ◽  
Vol 1006-1007 ◽  
pp. 437-440
Author(s):  
Wei Xuan Li ◽  
Chuan Li Zhao
Keyword(s):  
Single Machine ◽  
Window Size ◽  
Aging Effect ◽  
Single Machine Scheduling ◽  
Maintenance Activity ◽  
Starting Time ◽  
Actual Duration ◽  
Window Position ◽  
Due Window ◽  
Due Window Assignment

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.

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