Title
Single Machine Total Completion Time Minimization Scheduling With A Time-Dependent Learning Effect And Deteriorating Jobs
Abstract
In this article, we consider a single machine scheduling problem with a time-dependent learning effect and deteriorating jobs. By the effects of time-dependent learning and deterioration, we mean that the job processing time is defined by a function of its starting time and total normal processing time of jobs in front of it in the sequence. The objective is to determine an optimal schedule so as to minimize the total completion time. This problem remains open for the case of -1 < a < 0, where a denotes the learning index; we show that an optimal schedule of the problem is V-shaped with respect to job normal processing times. Three heuristic algorithms utilising the V-shaped property are proposed, and computational experiments show that the last heuristic algorithm performs effectively and efficiently in obtaining near-optimal solutions.
Year
DOI
Venue
2012
10.1080/00207721.2010.542837
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
Keywords
Field
DocType
scheduling, single machine, learning effect, deteriorating jobs, total completion time
Single-machine scheduling,Learning effect,Mathematical optimization,Heuristic,Multiprocessor scheduling,Computer science,Heuristic (computer science),Scheduling (computing),Minification,Dynamic priority scheduling
Journal
Volume
Issue
ISSN
43
5
0020-7721
Citations 
PageRank 
References 
19
0.64
15
Authors
3
Name
Order
Citations
PageRank
Jibo Wang174541.50
Mingzheng Wang225115.78
Ping Ji329618.86