Worst-case and numerical analysis of heuristic algorithms for flowshop scheduling problems with a time-dependent learning effect

2012 ◽  
Vol 184 (1) ◽  
pp. 282-297 ◽  
Author(s):  
Wen-Hung Kuo ◽  
Chou-Jung Hsu ◽  
Dar-Li Yang
Keyword(s):  
Numerical Analysis ◽  
Learning Effect ◽  
Heuristic Algorithms ◽  
Time Dependent ◽  
Scheduling Problems ◽  
Flowshop Scheduling ◽  
Worst Case ◽  
Dependent Learning

scholarly journals Flowshop Scheduling Problems with a Position-Dependent Exponential Learning Effect

2013 ◽  
Vol 2013 ◽  
pp. 1-5
Author(s):  
Mingbao Cheng
Keyword(s):  
Learning Effect ◽  
Flow Shop ◽  
Optimal Algorithm ◽  
Polynomial Time Algorithm ◽  
Performance Criteria ◽  
Flow Shop Scheduling ◽  
Scheduling Problems ◽  
Flowshop Scheduling ◽  
Worst Case ◽  
Special Cases

We consider a permutation flowshop scheduling problem with a position-dependent exponential learning effect. The objective is to minimize the performance criteria of makespan and the total flow time. For the two-machine flow shop scheduling case, we show that Johnson’s rule is not an optimal algorithm for minimizing the makespan given the exponential learning effect. Furthermore, by using the shortest total processing times first (STPT) rule, we construct the worst-case performance ratios for both criteria. Finally, a polynomial-time algorithm is proposed for special cases of the studied problem.

scholarly journals Group Scheduling Problems with Time-Dependent and Position-Dependent DeJong’s Learning Effect

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Li Sun ◽  
Lei Ning ◽  
Jia-zhen Huo
Keyword(s):  
Polynomial Time ◽  
Completion Time ◽  
Learning Effect ◽  
Time Dependent ◽  
Total Weighted Completion Time ◽  
Group Scheduling ◽  
Scheduling Problems ◽  
Scheduling Model ◽  
Proposed Model ◽  
Weighted Completion Time

In this paper, we introduce a group scheduling model with time-dependent and position-dependent DeJong’s learning effect. The objectives of scheduling problems are to minimize makespan, the total completion time, and the total weighted completion time, respectively. We show that the problems remain solvable in polynomial time under the proposed model.

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