Solving Job-Shop Scheduling Problems by a Novel Artificial Immune System

The optimization of job-shop scheduling is very important because of its theoretical and practical significance. This paper proposes an efficient scheduling method based on artificial immune systems. In the proposed method, the initial population is generated by a proposed scheduling initialization algorithm based on the G&T algorithm, and the models of the vaccination and receptor editing are designed to improve the immune performance. The approach is tested on a set of standard instances taken from the existing standard library. The simulation results validate the effectiveness of the proposed algorithm.