Online Rescheduling in Semiconductor Manufacturing

2010 ◽  
Vol 4 (2) ◽  
pp. 184-197 ◽  
Author(s):  
Masao Sugi ◽  
◽  
Mingang Cheng ◽  
Masashi Yamamoto ◽  
Hiroki Ito ◽  
...  

Semiconductor manufacturing rescheduling problems are difficult to solve in real time due to numerous disturbances. We focus on maintaining the existing schedule and propose online semiconductor manufacturing rescheduling. To handle temporary disturbances and obtain a new feasible schedule, our proposal revises the given schedule based on affected operation rescheduling with operation sorting (sorting-AOR) based on schedule stability. To reduce deadline violations, we propose improving schedules two or more days ahead based on a fast local search algorithm for semicritical paths. In problems with 200,000 processes, this handles disturbances and gets new feasible schedules and better revised schedules in less than 1 minute. This is more effective than conventional dispatching-rule-based approaches, some of which have been applied in different facilities because it provides higher schedule stability and fewer deadline violations.

2012 ◽  
Vol 6 (5) ◽  
pp. 741-751
Author(s):  
Hideki HASHIMOTO ◽  
Taichiro SUGIYAMA ◽  
Yuma TANAKA ◽  
Mutsunori YAGIURA

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Carolina Lagos ◽  
Guillermo Guerrero ◽  
Enrique Cabrera ◽  
Stefanie Niklander ◽  
Franklin Johnson ◽  
...  

A novel matheuristic approach is presented and tested on a well-known optimisation problem, namely, capacitated facility location problem (CFLP). The algorithm combines local search and mathematical programming. While the local search algorithm is used to select a subset of promising facilities, mathematical programming strategies are used to solve the subproblem to optimality. Proposed local search is influenced by instance-specific information such as installation cost and the distance between customers and facilities. The algorithm is tested on large instances of the CFLP, where neither local search nor mathematical programming is able to find good quality solutions within acceptable computational times. Our approach is shown to be a very competitive alternative to solve large-scale instances for the CFLP.


2018 ◽  
Vol 69 (6) ◽  
pp. 849-863 ◽  
Author(s):  
Ruizhi Li ◽  
Shuli Hu ◽  
Peng Zhao ◽  
Yupeng Zhou ◽  
Minghao Yin

2006 ◽  
Vol 14 (2) ◽  
pp. 223-253 ◽  
Author(s):  
Frédéric Lardeux ◽  
Frédéric Saubion ◽  
Jin-Kao Hao

This paper presents GASAT, a hybrid algorithm for the satisfiability problem (SAT). The main feature of GASAT is that it includes a recombination stage based on a specific crossover and a tabu search stage. We have conducted experiments to evaluate the different components of GASAT and to compare its overall performance with state-of-the-art SAT algorithms. These experiments show that GASAT provides very competitive results.


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