Scheduling Jobs with Truncated Exponential Sum-of-Logarithm-Processing-Times Based and Position-based Learning Effects

Yuan-Yuan Lu (), Fei Teng and Zhi-Xin Feng
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Yuan-Yuan Lu: College of Mathematics, Jilin Normal University, Siping, Jilin 136000, P. R. China
Fei Teng: College of Mathematics, Jilin Normal University, Siping, Jilin 136000, P. R. China
Zhi-Xin Feng: College of Mathematics, Jilin Normal University, Siping, Jilin 136000, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2015, vol. 32, issue 04, 1-17

Abstract: In this study, we consider a scheduling problem with truncated exponential sum-of-logarithm-processing-times based and position-based learning effects on a single machine. We prove that the shortest processing time (SPT) rule is optimal for the makespan minimization problem, the sum of the θth power of job completion times minimization problem, and the total lateness minimization problem, respectively. For the total weighted completion time minimization problem, the discounted total weighted completion time minimization problem, the maximum lateness minimization problem, we present heuristic algorithms (the worst-case bound of these heuristic algorithms are also given) according to the corresponding single machine scheduling problems without learning considerations. It also shows that the problems of minimizing the total tardiness, the total weighted completion time and the discounted total weighted completion time are polynomially solvable under some agreeable conditions on the problem parameters.

Keywords: Scheduling; truncated learning effect; worst-case bound; single machine (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (4)

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DOI: 10.1142/S0217595915500268

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