Genetic algorithms applied in BOPP film scheduling problems: minimizing total absolute deviation and setup times

Abstract The frequent changeovers in the production processes indicate the importance of setup time in many real-world manufacturing activities. The traditional approaches in dealing with setup times are that either to omit or to merge into the processing times so as to simplify the problems. These approaches could reduce the complexity of the problem, but often generated unrealistic outcomes because of the assumed conditions. This situation motivated us to consider sequence-dependent setup times in a real-world BOPP film scheduling problem. First, a setup time-based heuristic method was developed to generate the initial solutions for the genetic algorithms (GAs). Then, genetic algorithms with different mutation methods were applied. Extensive experimental results showed that the setup time-based heuristic method was relatively efficient. It was also found that a genetic algorithm with the variable mutation rate performed much effectively than one with the fixed mutation rate.