A Trajectory-Based Immigration Strategy Genetic Algorithm to Solve a Single-Machine Scheduling Problem with Job Release Times and Flexible Preventive Maintenance

This paper considers the single-machine problem with job release times and flexible preventive maintenance activities to minimize total weighted tardiness, a complicated scheduling for which many algorithms have been proposed in literature. However, considered problems are rarely solved by genetic (GAs), even though it has successfully various combinatorial optimization problems. For problem, we propose trajectory-based immigration strategy, where immigrant generation is based on given information of solution extraction knowledge matrices. We embed strategy into GA method improve population’s diversification process. To examine performance method, two versions methods (the without random immigration) mixed integer programming (MIP) model also developed. Comprehensive experiments demonstrate effectiveness comparing MIP methods. Overall, significantly outperforms other regarding quality due strategy.