Bicriterion total flowtime and maximum tardiness minimization for an order scheduling problem

2018 ◽  
Vol 117 ◽  
pp. 152-163 ◽  
Author(s):  
Chin-Chia Wu ◽  
Shang-Chia Liu ◽  
Tzu-Yun Lin ◽  
Tzu-Hsuan Yang ◽  
I-Hong Chung ◽  
...  
2021 ◽  
Vol 58 ◽  
pp. 291-305
Author(s):  
Chin-Chia Wu ◽  
Danyu Bai ◽  
Xingong Zhang ◽  
Shuenn-Ren Cheng ◽  
Jia-Cheng Lin ◽  
...  

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Jan-Yee Kung ◽  
Jiahui Duan ◽  
Jianyou Xu ◽  
I-Hong Chung ◽  
Shuenn-Ren Cheng ◽  
...  

In recent years, various customer order scheduling (OS) models can be found in numerous manufacturing and service systems in which several designers, who have developed modules independently for several different products, convene as a product development team, and that team completes a product design only after all the modules have been designed. In real-life situations, a customer order can have some requirements including due dates, weights of jobs, and unequal ready times. Once encountering different ready times, waiting for future order or job arrivals to raise the completeness of a batch is an efficient policy. Meanwhile, the literature releases that few studies have taken unequal ready times into consideration for order scheduling problem. Motivated by this limitation, this study addresses an OS scheduling model with unequal order ready times. The objective function is to find a schedule to optimize the total completion time criterion. To solve this problem for exact solutions, two lower bounds and some properties are first derived to raise the searching power of a branch-and-bound method. For approximate solution, four simulated annealing approaches and four heuristic genetic algorithms are then proposed. At last, several experimental tests and their corresponding statistical outcomes are also reported to examine the performance of all the proposed methods.


2016 ◽  
Vol 74 ◽  
pp. 175-186 ◽  
Author(s):  
Jianyou Xu ◽  
Chin-Chia Wu ◽  
Yunqiang Yin ◽  
Chuanli Zhao ◽  
Yi-Tang Chiou ◽  
...  

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