A SINGLE-MACHINE TWO-AGENT SCHEDULING PROBLEM BY GA APPROACH

Shuenn-Ren Cheng ()
Additional contact information
Shuenn-Ren Cheng: Graduate Institute of Business Administration, Cheng Shiu University, Kaohsiung County, Taiwan

Asia-Pacific Journal of Operational Research (APJOR), 2012, vol. 29, issue 02, 1-22

Abstract: A single-machine two-agent scheduling problem with a truncation learning effect is being addressed in the study. The truncation learning effect means that the actual processing time of a job is a function of the sum of processing times of already scheduled jobs and a control parameter. The aim is to find an optimal schedule to minimize the total weighted completion time of jobs of the first agent under the circumstances that no tardy job is allowed for the second agent. A branch-and-bound and three heuristic-based genetic algorithms (GAs) are proposed to solve the problem. Also presented in the study are the computational results of all proposed algorithms.

Keywords: Scheduling; two-agent; genetic algorithm; learning effect (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0217595912500133
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:apjorx:v:29:y:2012:i:02:n:s0217595912500133

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0217595912500133

Access Statistics for this article

Asia-Pacific Journal of Operational Research (APJOR) is currently edited by Gongyun Zhao

More articles in Asia-Pacific Journal of Operational Research (APJOR) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().