Self-adaptive memetic algorithms for multi-objective single machine learning-effect scheduling problems with release times

Author(s):  
Derya Deliktaş
Omega ◽  
2010 ◽  
Vol 38 (1-2) ◽  
pp. 3-11 ◽  
Author(s):  
Wen-Chiung Lee ◽  
Chin-Chia Wu ◽  
Peng-Hsiang Hsu

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Der-Chiang Li ◽  
Peng-Hsiang Hsu ◽  
Chih-Chieh Chang

The way to gain knowledge and experience of producing a product in a firm can be seen as new solution for reducing the unit cost in scheduling problems, which is known as “learning effects.” In the scheduling of batch processing machines, it is sometimes advantageous to form a nonfull batch, while in other situations it is a better strategy to wait for future job arrivals in order to increase the fullness of the batch. However, research with learning effect and release times is relatively unexplored. Motivated by this observation, we consider a single-machine problem with learning effect and release times where the objective is to minimize the total completion times. We develop a branch-and-bound algorithm and a genetic algorithm-based heuristic for this problem. The performances of the proposed algorithms are evaluated and compared via computational experiments, which showed that our approach has superior ability in this scenario.


2020 ◽  
Vol 156 ◽  
pp. 113445
Author(s):  
Danyu Bai ◽  
Hanyu Xue ◽  
Ling Wang ◽  
Chin-Chia Wu ◽  
Win-Chin Lin ◽  
...  

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