Solving job insertion problem in job shop scheduling using iterative improvement

The goal of this paper is to present a job-shop scheduling system based on iterative improvement to react to inconsistencies between a scheduling plan and the actual course of events on a shop floor. The iterative improvement approach starts with a complete but possibly infeasible schedule, it then applies local search technique to improve the schedule. The system described in this paper creates incrementally a reference (predictive) schedule and maintains the schedule, reacting to both conflict and opportunity. In this paper, we focus on job insertion problems, which arise frequently in dynamic and stochastic world. Experimental results show the efficiency and effectiveness of this approach