Multi-Objective Multi-Stage Optimize Scheduling Algorithm for Nonlinear Virtual Work-Flow Based on Pareto

Work-flow scheduling is for finding the allocation method to achieve optimal resource utilization. In process, constraints, such as time, cost and quality, need be considered. How balance these parameters a NP-hard problem, nonlinear manufacturing process increases difficulty of scheduling, so it necessary provide an effective heuristic algorithm. Aiming at problems, multi-objective virtual work-flow model was set up, staged optimization algorithm with objectives minimizing time maximizing quality proposed. The includes three phases: virtualization phase abstracts tasks services into nodes generate model; divides optimized segments obtains solution through reverse iteration; generation path according Pareto dominance. proposed performed 10.5% better in production than minimum critical algorithm, reduced meet constraint by 9.1% saves 13.7% more accuracy maximization