Rough mill component scheduling: Heuristic search versus genetic algorithms

Rough mill production systems cut lumber into smaller components needed to produce wood products. Because of the system's limited sorting capacity, rough mill operators need to schedule when different component sizes are made, a process called part scheduling and replacement. This scheduling process is significant because it greatly affects system performance. Three component scheduling algorithms are examined in this paper: a heuristic method that mimics how human operators manually schedule components; and two methods based on genetic algorithms, the Simple Genetic Algorithm and the Ordering Messy Genetic Algorithm. The performance of the algorithms is analyzed and tested on four cutting bills. Results show that the Ordering Messy Genetic Algorithm outperformed the Simple Genetic Algorithm, and heuristic component replacement performed better than replacement based on the genetic algorithm's objective function. Also, heuristic cut-list selection performed better on cutting bills with more short pieces, whereas GA cut-list selection performed better on bills with longer pieces.