NDLI: Unrelated parallel-machine scheduling to minimize total weighted completion time

Content Provider	Springer Nature Link
Author	Chen, Jeng Fung
Copyright Year	2013
Abstract	This research deals with the unrelated parallel-machine scheduling to minimize total weighted completion time. There are $$N$$ jobs, each having a weight and requiring a single stage of processing on one of the $$M$$ machines. Because of the attribute and mechanical structure of the machines, the processing time depends on both the job and the machine. A sequence-dependent setup time is required if the type of job scheduled is different from the previous one on the same machine. The required setup time depends on the previous job type, the current job type, and the machine on which the job is processed. Furthermore, the jobs (i.e., orders) from primary customers have rigid due date constraints. In this research, a revised SWPT and improvement procedures are applied to generate a feasible schedule. Three effective heuristics, two based on record-to-record travel (RRT1 and RRT2) and one based on random descent search, are developed to improve the feasible schedule. Computational performance of the proposed heuristics is evaluated through an extensive experiment. Computational results show that RRT1 performs better than the other two heuristics and is able to improve the initial solutions effectively. Computational experiences also indicate that RRT1 is capable of obtaining the optimal solutions for the small-size tested problems very efficiently.
Starting Page	1099
Ending Page	1112
Page Count	14
File Format	PDF
ISSN	09565515
Journal	Journal of Intelligent Manufacturing
Volume Number	26
Issue Number	6
e-ISSN	15728145
Language	English
Publisher	Springer US
Publisher Date	2013-10-31
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Record-to-record travel Setup time Total weighted completion time Unrelated parallel machine Production Manufacturing, Machines, Tools Control, Robotics, Mechatronics
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Artificial Intelligence Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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