Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/21355
Title: A two-agent single-machine scheduling problem with truncated sum-of-processing-times-based learning considerations
Authors: Cheng, TCE 
Cheng, SR
Wu, WH
Hsu, PH
Wu, CC
Keywords: Scheduling
Simulated annealing
Truncated sum-of-processing-times- based learning
Two-agent
Issue Date: 2011
Publisher: Pergamon Press
Source: Computers and industrial engineering, 2011, v. 60, no. 4, p. 534-541 How to cite?
Journal: Computers and industrial engineering 
Abstract: Scheduling with learning effects has received a lot of research attention lately. By learning effect, we mean that job processing times can be shortened through the repeated processing of similar tasks. On the other hand, different entities (agents) interact to perform their respective tasks, negotiating among one another for the usage of common resources over time. However, research in the multi-agent setting is relatively limited. Meanwhile, the actual processing time of a job under an uncontrolled learning effect will drop to zero precipitously as the number of jobs increases or a job with a long processing time exists. Motivated by these observations, we consider a two-agent scheduling problem in which the actual processing time of a job in a schedule is a function of the sum-of-processing-times-based learning and a control parameter of the learning function. The objective is to minimize the total weighted completion time of the jobs of the first agent with the restriction that no tardy job is allowed for the second agent. We develop a branch-and-bound and three simulated annealing algorithms to solve the problem. Computational results show that the proposed algorithms are efficient in producing near-optimal solutions.
URI: http://hdl.handle.net/10397/21355
ISSN: 0360-8352
EISSN: 1879-0550
DOI: 10.1016/j.cie.2010.12.008
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