The Research of Flexible Job Shop Scheduling Problem in Uncertain Environment

Abstract

The general genetic algorithm is difficult to obtain the optimal solution in the uncertain flexible workshop environment, there is often a variety of uncertain interference events that obstructive to production scheduling. An improved genetic algorithm is introduced to solve the production scheduling model. On this basis, an Event-driven Strategy and Changed-cycle-driven Strategy that can cope with unexpected situations is proposed to cope with dynamic changes in the production environment. When interference occurs, trigger the rescheduling mechanism to reduce interference effects. Finally, a case study of a company is carried out to demonstrate that the above research can get a satisfactory scheduling plan.