Minimizing Makespan in Job Shop Scheduling Problem Using Genetic Algorithm

2015 ◽  
Vol 813-814 ◽  
pp. 1183-1187 ◽  
Author(s):  
Aathi Muthiah ◽  
R. Rajkumar ◽  
B. Muthukumar

- Scheduling is an important tool for manufacturing and engineering, where it can have a major impact on the productivity of a process. In manufacturing, the purpose of scheduling is to minimize the production time and costs. Production scheduling aims to maximize the efficiency of the operation and reduce costs. We keep all of our machines well-maintained to prevent any problems, but there is on way to completely prevent down-time. With redundant machines we have the security of knowing that we are not going to be in trouble meeting our deadlines if a machine has any unexpected down-times. Finally we can work to get our batch sizes as small as is reasonably possible while also reducing the setup time of each batch. This allows us to eliminate a sizable portion of each part waiting while the rest of the parts in the batch are being machined.

2012 ◽  
Vol 629 ◽  
pp. 730-734 ◽  
Author(s):  
Cun Liang Yan ◽  
Wei Feng Shi

Job shop scheduling problem (JSP) is the most typical scheduling problem, In the process of JSP based on genetic algorithm (GA), large amounts of data will be produced. Mining them to find the useful information is necessary. In this paper dividing, hashing and array (DHA) association rule mining algorithm is used to find the frequent itemsets which contained in the process, and extract the corresponding association rules. Concept hierarchy is used to interpret the rules, and lots of useful rules appeared. It provides a new way for JSP study.


2011 ◽  
Vol 201-203 ◽  
pp. 795-798
Author(s):  
Jun Xing Xiong ◽  
Jin Ping Zhao ◽  
Hai Ning Tu

Aiming at Job Shop Scheduling Problem with Minimal Makespan, This paper is designed to use genetic algorithm to solve the problem of job shop scheduling, and also achieves the algorithm by using the C#. Application shows that the genetic algorithm to solve job shop scheduling problem is efficient and has good application value.


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