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

Abstract:

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.

• Periodical: Advanced Materials Research (Volume 629)
• Pages: 730-734
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.629.730
• Online since: December 2012
• Authors: Cun Liang Yan, Wei Feng Shi
• Keywords: Asscoiation Rule Mining, Data Mining (DM), Genetic Algorithm (GA), Job Shop Scheduling

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