The research on job shop on-line scheduling with random release-date

For the job shop on-line scheduling in which the release dates of jobs are stochastic distributed, the hybrid scheduling strategy that integrates the interval rolling mechanism with the key event-driven is introduced. The satisfactory solution can be obtained through iterative optimization by embedding the neighborhood search into the constraint satisfaction solving procedure. The simulation and computational results verified that the scheduling method proposed in the paper can meet the requirements of both efficiency and stability.

I. INTRODUCTION

Compared with the off-line scheduling in which all related tasks information have been pre-determined at the decision point, the job shop on-line scheduling fully represents the dynamic stochastic characteristic of modern scheduling. In the solving procedure, the original problem constantly varies because of the additions or deletions of the new variables and constraints. The existing methods, which usually focus on the static model, can hardly apply to the production environment in which the factors of job attributes, the resources availability and etc are randomly distributed [1] [2].