Association Rule Mining for Job Shop Scheduling Problem Based on Genetic Algorithm

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.

[1]  Tomasz Imielinski,et al.  Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.

[2]  Ling Wang,et al.  A Modified Genetic Algorithm for Job Shop Scheduling , 2002 .

[3]  Mohammad Bagher Fakhrzad,et al.  Solving flexible flow-shop problem with a hybrid genetic algorithm and data mining: A fuzzy approach , 2011, Expert Syst. Appl..

[4]  燕存良,et al.  A New Hybrid Algorithm for Association Rule Mining , 2007 .

[5]  Lawrence Davis,et al.  Job Shop Scheduling with Genetic Algorithms , 1985, ICGA.

[6]  Sönke Hartmann,et al.  A self‐adapting genetic algorithm for project scheduling under resource constraints , 2002 .

[7]  Mitsuo Gen,et al.  A hybrid of genetic algorithm and bottleneck shifting for multiobjective flexible job shop scheduling problems , 2007, Comput. Ind. Eng..

[8]  Zhu Kai-yu.  A New Hybrid Algorithm for Association Rule Mining , 2007 .

[9]  Debarshi Barat,et al.  Job Scheduling with Genetic Algorithm , 2013 .

[10]  D. Y. Sha,et al.  Using Data Mining for Due Date Assignment in a Dynamic Job Shop Environment , 2005 .

[11]  Jinwei Gu,et al.  A novel competitive co-evolutionary quantum genetic algorithm for stochastic job shop scheduling problem , 2010, Comput. Oper. Res..

[12]  Jiaquan Gao,et al.  A new parallel genetic algorithm for solving multiobjective scheduling problems subjected to special process constraint , 2009 .

[13]  Liang Gao,et al.  Integration of process planning and scheduling - A modified genetic algorithm-based approach , 2009, Comput. Oper. Res..

[14]  Xiao Wei.  Data mining algorithm based on genetic algorithm and its application , 2009 .