scholarly journals Due-Window Assignment and Resource Allocation Scheduling with Truncated Learning Effect and Position-Dependent Weights

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Shan-Shan Lin
Keyword(s):  
Resource Allocation ◽  
Learning Effect ◽  
Window Size ◽  
Scheduling Problems ◽  
Polynomial Time Algorithms ◽  
Consumption Cost ◽  
Optimality Properties ◽  
Due Window ◽  
Due Window Assignment ◽  
Time Resource

This paper studies single-machine due-window assignment scheduling problems with truncated learning effect and resource allocation simultaneously. Linear and convex resource allocation functions under common due-window (CONW) assignment are considered. The goal is to find the optimal due-window starting (finishing) time, resource allocations and job sequence that minimize a weighted sum function of earliness and tardiness, due window starting time, due window size, and total resource consumption cost, where the weight is position-dependent weight. Optimality properties and polynomial time algorithms are proposed to solve these problems.

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.

SINGLE MACHINE SCHEDULING WITH A LEARNING EFFECT AND A RATE-MODIFYING ACTIVITY

2011 ◽  
Vol 28 (04) ◽  
pp. 511-521 ◽  
Author(s):  
CHUANLI ZHAO ◽  
HENGYONG TANG
Keyword(s):  
Single Machine ◽  
Processing Time ◽  
Learning Effect ◽  
Window Size ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Scheduling Problems ◽  
Polynomial Time Algorithms ◽  
Due Window ◽  
Machine Scheduling Problems

In the paper, single machine scheduling problems with a learning effect and a rate-modifying activity are considered. Under the learning effect, the processing time of a job is a decreasing function of its position in the sequence. The rate-modifying activity is an event that can change the speed of the machine, and hence the processing time of jobs after the activity. The following objective functions are considered: the makespan, the total earliness, tardiness and completion time penalty, and the total earliness, tardiness, due-window starting time and due-window size penalty. Polynomial time algorithms are proposed to optimally solve the problems.

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.

COMMON DUE-WINDOW ASSIGNMENT AND SCHEDULING OF JOB-DEPENDENT DETERIORATING JOBS AND MULTIPLE DETERIORATING MAINTENANCE ACTIVITIES

2014 ◽  
Vol 31 (01) ◽  
pp. 1450004 ◽  
Author(s):  
XINGONG ZHANG
Keyword(s):  
Operations Management ◽  
Production Scheduling ◽  
Window Size ◽  
Deteriorating Jobs ◽  
Planning Horizon ◽  
Scheduling Problems ◽  
Deteriorating Maintenance ◽  
Due Window ◽  
Maintenance Activities ◽  
Due Window Assignment

Due-window assignment and production scheduling problems are important issues in operations management. In this paper, the problems of common due-window assignment and scheduling of job-dependent deteriorating jobs and multiple deteriorating maintenance activities simultaneously on a single-machine are investigated. We assume that the machine may be subjected to several maintenance activities during the planning horizon. However, due to the restriction of budget of maintenance, the upper bound of the maintenance frequency on the machine is assumed to be known in advance. Moreover, we assume that the duration of each maintenance activity depends on the running time of the machine. Polynomial time algorithms for the all the studied problems are provided, where the objective is to simultaneously minimize the earliness, tardiness, due-window starting time, and due-window size costs.

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.

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.

Flow Shop Resource Allocation Scheduling with Due Date Assignment, Learning Effect and Position-Dependent Weights

2020 ◽  
Vol 37 (03) ◽  
pp. 2050014
Author(s):  
Wei-Wei Liu ◽  
Chong Jiang
Keyword(s):  
Resource Allocation ◽  
Learning Effect ◽  
Flow Shop ◽  
Due Date ◽  
Due Date Assignment ◽  
Polynomial Time Algorithms ◽  
Optimality Properties ◽  
No Wait ◽  
Special Case ◽  
Order Algorithm

In this paper, the flow shop resource allocation scheduling with learning effect and position-dependent weights on two-machine no-wait setting is considered. Under common due date assignment and slack due date assignment rules, a bi-criteria analysis is provided. The optimality properties and polynomial time algorithms are developed to solve four versions of the problem. For a special case of the problem, it is proved that the problem can be optimally solved by a lower order algorithm.

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