A supervised self-organizing approach for large-scale multistage batch scheduling problems

Abstract

This paper presents a supervised self-organizing approach for solving the scheduling problems of large-scale multistage batch plants. The proposed approach is based on a supervised self-organizing model, which consists of a self-organizing scheduling system and a supervisory unit. Four types of self-organizing units are defined in the self-organizing scheduling system and they can be guided by the supervisory unit in a global perspective. A supervised self-organizing algorithm, in which minimum makespan is selected as the scheduling objective, is also proposed to solve the supervised self-organizing model. An illustrative example has been efficiently solved. Compared with MILP approach, the proposed approach shows its superiority in solving large-scale complex problems.