Apriori, Association Rules, Data Mining,Frequent Itemsets Mining (FIM), Parallel Computing

The job-shop scheduling problem is concerned with allocating limited resources to operations over time. Although the job shop scheduling has an important role in various fields, it is one of the most difficult problems in combinational optimization. In this paper, we propose a new scheduling technique that combines Ant Colony Optimization (ACO) with GT method in order to realize effective scheduling. ACO approach has been applied recently to several combinational optimization problems, e.g., TSP and scheduling problem. However, no studies have ever seen the approach of applying hybrid ACO to job-shop problems. Experimental results using benchmark data show improvement comparison with a conventional scheduling technique.