Modeling and simulation of stochastic double-objective scheduling problem in welding workshop

The scheduling problem was based on a real welding workshop in a large manufacturing enterprise. A stochastic scheduling problem consisting of m workers and n jobs was dealt with and a mathematic model was developed to minimize maximum expected value and variance of the completion time. In order to solve the problem, Binary Particle Swarm Optimization (BPSO) algorithm was modified, and a dynamic neighborhood strategy, new particle memory updating, and one-dimension optimization method were used to solve two objectives problem. A simulation example was carried out to illustrate that the improved method could efficiently find Pareto front solutions.